Suspension control device, vehicle comprising said device, production method thereof and associated program

ABSTRACT

The invention relates to a device for controlling the suspension of the body shell of a motor vehicle. The inventive device comprises a calculator (CSS) which can calculate a control value (ER) for an actuator (M) of a shock absorber (AM) of the suspension (S) as a function of at least one modal body shell speed calculated from a modal body shell acceleration. The invention is characterized by a sensor (CAP-DEB) for sensing wheel (A,B, C, D) travel in relation to the body shell, which is connected to a first means (CAL) for calculating the modal body shell acceleration from the travel measurement (DEB) provided by the sensor (CAP-DEB).

The invention relates to a suspension control device for a motorvehicle.

A field of application of the invention relates to motor vehicles havinga spring suspension, a hydropneumatic suspension or another type ofsuspension.

These suspensions have a damper on each wheel that uses a law ofvariable damping that can be set by an actuator controlled by a computeron board the vehicle.

The computer receives input measurements provided by sensors, andcalculates the command magnitude or magnitudes for the damper actuatorstherefrom.

The computer particularly takes into account the accelerations to whichthe vehicle body is subjected during travel, such as heave modalacceleration in the vertical direction, roll modal acceleration about alongitudinal axis, and pitch modal acceleration about a transverse axis.

The computer uses integration to calculate the corresponding modalvelocities of the body.

Devices are known in which the computer implements a control process tomake the vertical modal velocity of heave, the angular modal velocity ofroll and the angular modal velocity of pitch tend toward zero; thislogic is commonly called “Skyhook”, and makes it possible to improve thecomfort of the people in the car.

Such devices are known which use three accelerometers to measure thethree modal accelerations.

These accelerometers measure each an acceleration along a determineddirection and they must be implanted in a very precise way in thevehicle, in order to provide a reliable measure of the modalaccelerations and to avoid distorting the instructions sent by thecomputer to the actuators.

Additionally, each accelerometer installed on the vehicle is relativelyexpensive.

An objective of the invention is to obtain a suspension control devicethat remedies the drawbacks of the state of the art and that can dowithout accelerometers for calculating at least one body modal speed ina reliable way.

To this effect, a first object of the invention is a suspension controldevice with variable damping for a motor vehicle body on its wheels,having a computer adapted to calculate a control magnitude of anactuator of at least one damper with variable damping of the suspensionas a function of at least one body modal speed calculated from at leastone body modal acceleration determined on the vehicle,

characterized in that

it further comprises at least one sensor of the displacement of a wheelwith respect to the vehicle body, connected to a first means forcalculating the body modal acceleration from the displacementmeasurement provided by the displacement sensor.

Thus, the invention makes it possible to use the displacement sensorspresent on the wheels to estimate the body modal accelerations in realtime. The invention, not only avoids the expense of threeaccelerometers, but also, eliminates the bulk caused by these threeaccelerometers mounted in the body of the vehicle in predeterminedlocations thereof.

According to other characteristics of the invention,

-   -   the first means for calculating the body modal acceleration        comprises an estimator of at least one force exerted by the        suspension of said wheel on the body as a function of at least        the displacement measurement provided by the displacement        sensor, and a second means for calculating the body modal        acceleration as a function of at least the suspension force        provided by said suspension force estimator;    -   the suspension force estimator comprises:

a derivator module calculating a displacement speed from a displacementmeasurement provided by the displacement sensor,

an estimator of a damping force of the damper as a function of thedisplacement speed provided by the derivator module and the memorizedcurrent damping law of the damper,

an estimator of a dry friction force as a function of the displacementspeed,

an estimator of a flexure force of suspension springs and stops as afunction of the displacement value and a determined static attitude ofthe body;

-   -   the estimator of the dry friction force is a hyperbolic        tangential (tan h) or circular tangent (tg) function of the        displacement speed divided by a fixed value, this function being        multiplied by a prescribed multiplying factor;    -   the estimator of the flexure force of suspension springs and        stops comprises:

a module for calculating the static attitude of the vehicle as afunction of the displacement value,

an adder for calculating a summed value of the displacement value andthe static attitude,

a module for calculating an absolute flexure force of suspension springsand stops as a function of said summed value,

a module for calculating a static flexure force on said wheel as afunction of the static attitude,

a subtractor providing said flexure force of suspension springs andstops by subtracting the static flexure force from the absolute flexureforce of suspension springs and stops;

-   -   a displacement sensor is provided for each of the two front        wheels and the two rear wheels, and the module for calculating        the static attitude has a means for calculating the front static        attitude and the rear static attitude of the vehicle, as being        the mean displacement of the front wheel displacements and the        rear wheel displacements, respectively, filtrated by a low-pass        filter, a front attitude offset constant and a rear attitude        offset constant, respectively, being added to this filtered mean        displacement;    -   the first calculation means further comprises an estimator of a        roll torque and/or an estimator of a pitch torque;    -   the first calculation means has:

a means for calculating a transverse acceleration reset value RECT,

a sensor of the vehicle body transverse acceleration ACCT;

the roll torque estimator calculating said roll torque c_(θ) using theformula:c _(θ)=(ACCT−RECT)·(MTOT)·d(G,CR)

where MTOT is the vehicle mass, and

d(G, CR) is the predetermined distance between the center of gravity ofthe body and its roll center,

-   -   the first calculation means (CAL) has:

a means for calculating a longitudinal acceleration reset value RECL,

a sensor of the longitudinal acceleration ACCL of the vehicle body,

the estimator of the pitch torque calculating said pitch torque c_(φ)using the formula:c _(φ)=(ACCL−RECL)·(MTOT)·hG+c _(φB),where MTOT is the vehicle mass,

hG is the predetermined height between the center of gravity of the bodyand its pitch center, and C_(φB) is the component of the pitch torqueattributable to the Brouilhet effect;

-   -   the component c_(φB) of the pitch torque attributable to the        Brouilhet effect is calculated as a function of a braking        information unit provided by a determination module as a        function of a master cylinder pressure value provided by a        master cylinder pressure sensor;    -   the device comprises a first filter that eliminates at least the        low frequencies of the body modal acceleration provided by the        first calculation means and a third means for calculating the        body modal speed from the filtered body modal acceleration        provided by the first filter;    -   the low cutoff frequency of the first filter is greater than or        equal to 0.1 Hz;    -   the first means for calculating the body modal acceleration        comprises a second filter that eliminates at least the low        frequencies from the displacement measurement provided by the        displacement sensor;    -   the low cutoff frequency of the second filter is greater than or        equal to 0.2 Hz;    -   the control magnitude is a damping law determined from a        plurality of different damping laws that impose the damper force        as a function of its displacement speed.

A second object of the invention is a motor vehicle having a body,wheels, a suspension of the body on the wheels, and a suspension controldevice as described above.

A third object of the invention is a production method for a motorvehicle,

the motor vehicle being equipped with wheels, a body, a suspensionhaving at least one damper with variable damping of the body on thewheels, and a suspension control device, the control device having atleast one computer adapted to calculate a control magnitude of anactuator of said at least one suspension damper,

the production method having a step in which the computer is mounted onthe vehicle,

characterized in that the production method has

at least one computer programming step using at least one program havingprogram instructions that employ the calculating means of the suspensioncontrol device as described above.

A fourth object of the invention is a computer program for controlling acomputer, having program instructions for calculating the body modalacceleration from the displacement measurement provided by the wheeldisplacement sensor, for calculating the body modal velocity as afunction of at least this body modal acceleration, and for calculatingthe control magnitude of the actuator as a function of this body modalspeed, when it is employed in a suspension control device as describedabove.

The invention will be more easily understood by reading the followingdescription, given only as a non-limiting example, with reference to theattached drawings, in which:

FIG. 1 is a schematic perspective view of a suspension device of a frontaxle of a vehicle,

FIG. 2 is a functional diagram showing the suspension control device,

FIG. 3 is a schematic perspective view of a vehicle body equipped withthe suspension on its wheels,

FIG. 4 is a modular block diagram of a modal velocity calculation unitof the control device according to the invention,

FIG. 5 is a modular block diagram of an estimator provided in thecontrol device according to FIG. 4,

FIG. 6 is a modular block diagram of a Skyhook-type unit for calculatingmodal forces,

FIG. 7 is a modular block diagram of a unit for calculating a front- andrear-sprung mass,

FIG. 8 is a flow chart of the sprung-mass calculation method of the unitaccording to FIG. 7,

FIG. 9 is a modular block diagram of a unit for calculating levels ofmovement and bouncing of the body,

FIG. 10 is a modular block diagram of a Roadhook-type unit forcalculating modal forces,

FIG. 11 is a modular block diagram of a unit for calculatinganticipatory modal force terms,

FIG. 12 is a modular block diagram of a unit for calculating setpointforces at the wheels, including the Skyhook-type unit for calculatingmodal forces and the Roadhook-type unit for calculating modal forces,

FIG. 13 shows flow charts of demand detection signals and of anintermediate weighting coefficient calculated as a function thereof, tobe used in the calculation unit according to FIG. 12,

FIG. 14 shows flow charts of the angle of the steering wheel duringsimple cornering, and of a weighting coefficient between the Skyhookforces and the Roadhook forces, to be used in the calculation unitaccording to FIG. 12,

FIG. 15 shows damping laws for the suspension's variable dampers,

FIG. 16 is a modular block diagram of a unit for calculating a dampingsetpoint law if an impact is detected,

FIG. 17 is a modular block diagram of a unit for calculating a dampingsetpoint law if a large amplitude body movement is detected,

FIG. 18 is a transverse section diagram showing the connection of adisplacement sensor to the body and to a front or rear wheel.

In FIGS. 1 to 3, the vehicle 1 has a body 2 mounted on four wheels,namely, a left front wheel A, a right front wheel B, a right rear wheelC, and a left rear wheel D.

Each wheel A, B, C, D is connected to the body 2 by its own suspensionsystem S with a spring R between two stops, but it could also be ahydropneumatic suspension.

Each suspension system S has a damper AM equipped with an actuator Mcontrolled by an onboard computer CSS.

This actuator M is a motor, for example, that makes it possible tochange the oil passage section in the damper AM. Thus, to each oilpassage section in the damper corresponds a different damping law of thelatter. These damping laws, also called damping states, are memorized inthe form of curves, tables of values, mathematical formulas orotherwise. FIG. 15 shows these damping laws ER, where each damping lawis a predetermined curve of the force exerted by the damper toward thebody as a function of the displacement speed VDEB of this damper AM,with increasingly stiff laws having greater forces at a constantdisplacement speed. As an example, the damping states ER are numbered inincreasing order for increasingly stiff damping states, i.e.,corresponding to an increasingly greater damping force at a constantdisplacement speed VDEB. Thus, a minimum damping state corresponds to adamping state having a minimal stiffness, i.e., corresponding to adamping force greater than or equal to a minimum for each displacementspeed VDEB.

The computer CSS is connected to the vehicle network CAN in order toretrieve a large share of the useful signals (vehicle speed, ABSregulation, lateral and longitudinal accelerations provided by thebraking system, sportive mode requested by the driver, supplied by auser interface (built-in systems interface), etc.). It also uses its ownsensors (direct wire connections with the sensors) to gauge themovements of the car at each instant. Lastly, it is connected to theactuators, which it controls.

The motor can be a stepper motor, in which case the damper AM has a setnumber N of discrete damping laws, or a direct current servomotor withposition control, in which case the damper AM has an infinite number ofdamping laws.

For example, the stepper motor actuator can take nine distinct stablepositions, which makes it possible to have nine damping laws, from softto stiff. That is, the smaller the oil passage section, the greater thedamping force and the stiffer the damper.

There can be stable laws and unstable laws. For stable laws, it is amatter of controlling the stepper motor so that it finds its angularsetpoint value. Once the control process has ended, the stable-lawactuator remains in this position even if it is no longer under power.Conversely, for unstable laws, the motor must be kept under power inorder to remain in this law. For example, in one embodiment, there areboth stable laws and unstable laws, e.g., with the unstable laws beingpositioned between consecutive stable laws. For example, in FIG. 15,nine stable laws and eight unstable laws are present. In anotherembodiment, all the laws are stable, e.g., with 16 stable laws.

Each actuator M has a control input COM connected to the computer CSS soas to receive from the latter a control magnitude ER selecting aposition of the actuator M from among multiple positions, in order toapply a preset damping law corresponding to this position.

According to the invention, a displacement sensor CAP-DEB is provided onat least one of the vehicle wheels A, B, C, D, and preferably on eachwheel A, B, C, D. Each sensor CAP-DEB thus measures the displacement DEBof its associated wheel with respect to the body 2.

The wheel displacement sensors CAP-DEB are angular, for example, andgive the instantaneous value of the angle between the wheel rotationaxle and the body 2. For example, in FIGS. 1 and 18, each displacementsensor CAP-DEB has a fixed part CAPF such as a housing, attached to thebody 2, and a mobile part CAPM connected to an element attached to thewheel. A connecting rod BIEL joins the mobile part CAPM to the fixedpart CAPF and drives the rotation of an angular measurement member MEScontained in the fixed part CAPF when the wheel moves up or downrelative to the body 2. The mobile part CAPM is fixed on a supportingelement SUP for the wheel rotation axle AX, for example. This supportingelement SUP is mobile about an axis SUPL that is substantiallylongitudinal relative to the body 2. The mobile part CAPM is fixed onthe supporting element SUP at a distance from its rotation axis SUPL.

The displacement measurements DEB for the wheels A, B, C, D are sentfrom the sensors CAP-DEB to the computer CSS, which has correspondinginputs E-DEB.

Modal Accelerations

From the wheel displacement measurements DEB, the computer CSScalculates the heave modal acceleration {umlaut over (z)}G of the body,the angular roll modal acceleration {umlaut over (θ)} and the angularpitch modal acceleration {umlaut over (φ)} with the formulas below.

$\quad\left\{ \begin{matrix}{{\overset{¨}{z}G} = \frac{{FA} + {FB} + {FC} + {FD}}{M}} \\{\overset{¨}{\theta} = \frac{{\frac{v}{2}\left( {{FB} + {FC} - {FA} - {FD}} \right)} + C_{BAD} + C_{\theta}}{I_{\theta}}} \\{\overset{¨}{\varphi} = \frac{{\left( {e - \lg} \right)\left( {{FC} + {FD}} \right)} - {\lg\left( {{FA} + {FB}} \right)} + C_{\varphi}}{I_{\varphi}}}\end{matrix} \right.$

where G is the center of gravity of the body 2, zG is the altitude of Gin an ascending vertical direction Z, θ is the roll angle of the body 2around a longitudinal axis X passing through G and oriented from therear toward the front, φ is the pitch angle of the body 2 around atransverse axis passing through G and oriented from right to left, withaxes X, Y, Z forming an orthonormal reference.

FA, FB, FC, FD are the forces exerted by the respective wheels A, B, C,D on the body 2 via their suspensions S.

v is the track width of the body 2, that is, the distance between theright wheels and the left wheels in the transverse direction,

e is the wheel base of the vehicle,

lg is the longitudinal distance between the center of gravity G and thetransverse axle of the front wheels A and B,

M is the predetermined mass of the body 2 with no vehicle occupant.

I_(θ) is the roll moment of inertia, and I_(φ) is the pitch moment ofinertia.

CBAD is a torque exerted by the anti-roll bar BAD on the body 2.

C_(θ) is a roll torque, and C_(φ) is a pitch torque.

Described below are the various calculation means used in implementingthe control method according to the invention.

The method of calculating modal accelerations in the computer CSS isimplemented by module 10 shown in FIGS. 4 and 5, for example.

The module blocks described in the figures are implemented in thecomputer CSS using any appropriate automatic means, software inparticular.

Module 10 has a first calculation means CAL for the modal accelerations{umlaut over (z)}G, {umlaut over (θ)} and {umlaut over (φ)}, whichreceives the wheel displacement measurements DEB as input.

The calculation means CAL comprises:

-   -   an estimator 11 for the torque C_(BAD) generated by the        anti-roll bar BAD,    -   an estimator 12 of the forces FA, FB, FC, FD exerted by the        respective wheels A, B, C, D on the body 2,    -   a filter 13 for the displacement measurement DEB sent as input        to the calculation means CAL.

The filter 13 eliminates the low frequencies from the displacementmeasurement DEB provided by the sensors CAP-DEB.

For example, this filter 13 has a high-pass filter with a low cutofffrequency greater than or equal to 0.2 Hz. The filter 13 can be embodiedas a bandpass filter that additionally has a high cutoff frequency,e.g., greater than or equal to 8 Hz, which makes it possible to retainan adequately constant phase in the bandwidth.

The filtered wheel displacement DEBF provided at the filter 13 outputfrom the wheel displacement measurement DEB is sent to the estimator 11input, and to another estimator 12 input. From the four displacementmeasurements DEB(A), DEB(B), DEB(C), DEB(D) provided by the sensorsCAP-DEB on the respective wheels A, B, C, D, the filter 13 provides fourfiltered displacement measurements DEBF(A), DEBF(B), DEBF(C), DEBF(D).

Anti-Roll Bar

The estimator 11 calculates the anti-roll bar torque C_(BAD) as afunction of the filtered displacement values DEBF provided by the filter13 as follows:

-   -   for the left front wheel:        C _(BAD)(A)=(DEBF(A)−DEBF(B))·(Kbadav)/v ²,    -   for the right front wheel:        C _(BAD)(B)=−C _(BAD)(A),    -   for the left rear wheel:        C _(BAD)(D)=(DEBF(D)−DEBF(C))·(Kbadar)/v ²,    -   for the right rear wheel:        C _(BAD)(C)=−C _(BAD)(D),    -   where Kbadav is a predetermined parameter corresponding to the        stiffness of the front anti-roll bar BAD,    -   Kbadar is a predetermined parameter corresponding to the        stiffness of the rear anti-roll bar, not shown.

Suspension Load

The suspension load estimator 12 has an input for the filtereddisplacements DEBF, an input for the unfiltered displacements DEB, aninput for the actual state ER of the actuator, meaning the damping lawER it is currently implementing, this actual state and its changes beingmemorized, for example, an input DEAV for static front wheel load and aninput DEAR for static rear wheel load.

This estimator 12 is described below in FIG. 5 as an example forcalculating the suspension load FA on the left front wheel A. Of course,the calculation is comparable for the other loads FB, FC, FD, replacingthose elements relating specifically to wheel A with valuescorresponding to wheel B, C, or D.

In the estimator 12, the displacement DEB(A) measured by the sensorCAP-DEB on the wheel A is sent to a low-pass filter PB that limits thebandwidth of the displacement DEB(A), followed by a derivation moduleDER to obtain the displacement speed VDEB for wheel A. The displacementspeeds VDEB of the wheels are provided at an output of the estimator 12and the module 10.

A calculation module MFAM for the damping force FAM exerted by thedamper AM on the body 2 receives as input the actual state ER and thedisplacement speed VDEB of the wheel in question. The damping laws forthe dampers AM are memorized in advance, for example, or they can berecalculated once the state ER has been specified. With each of thedamping laws ER, the displacement speed VDEB can be calculated ordetermined as a function of the damping force FAM exerted by the damperAM, and vice versa. From the state ER, the module MFAM determines thedamping law currently in use for the wheel A damper AM, and from thewheel A displacement speed VDEB(A) for this selected law, the moduledetermines the wheel A damping force FAM, e.g., by reading the curve forthis law.

Another module MFSEC for calculating a dry friction force FSEC for thewheel A damper AM also receives the wheel A displacement speed VDEB asinput and calculates the dry friction force FSEC using the followingformula:Fsec=(FsAv)·ta nh(VDEB/10⁻²)

where VDEB is in cm/s and FsAv is a dry friction coefficient for thefront wheels, previously calculated on a test bench, and equal to around200 Newtons, for example.

This friction coefficient is replaced with a friction coefficient FsArfor the rear wheels.

Static Characteristics Estimator

A module MAS for calculating the static attitude AS receives thedisplacements DEB of the four wheels A, B, C, D as input, and from thelatter, it calculates the static attitude AS, which represents thestatic equilibrium point of the suspension S when the vehicle isimmobile on a horizontal surface. This module MAS calculates a frontstatic attitude ASav and a rear static attitude ASar. The front staticattitude ASav, for example, can be calculated as the mean displacementDEBAVMOY (half-sum) of the displacements DEB of the front wheels A, B,filtered through a low-pass filter, e.g., a second-orderButterworth-type filter, and then a front attitude offset constant isadded to this filtered mean displacement. The rear static attitude ASar,for example, can be calculated as the mean displacement DEBARMOY(half-sum) of the displacements DEB of the rear wheels C, D, filteredthrough a low-pass filter, e.g., a second-order Butterworth-type filter,and then a rear attitude offset constant is added to this filtered meandisplacement. It is assumed that the displacement sensor CAP-DEB iscalibrated to measure the displacement with respect to this staticattitude AS. An adder AD1 adds the filtered displacement DEBF-A forwheel A to the static attitude AS calculated for wheel A, i.e., thefront static attitude, to obtain the actual length LR of the spring Rassociated with wheel A.

The module MAS for calculating the static attitude AS is, for example,part of a static characteristics estimator 20 shown in FIG. 6, whichreceives as input the displacements DEB of the four wheels A, B, C, D, afront static pressure and a rear static pressure in the case of ahydropneumatic suspension, the vehicle speed VVH, and an opening panelinformation unit 10. The vehicle speed VVH is provided by a speedsensor, for example, or any other calculation means.

The static characteristics estimator 20 includes:

-   -   a means for calculating a front apparent dynamic mass MDAAV and        a rear apparent dynamic mass MDAAR as a function of the        displacements DEB,    -   a means for calculating a front aerodynamic bias BAAV and a rear        aerodynamic bias BAAR from the vehicle speed VVH,    -   a means for calculating the vehicle's sprung mass MSUS and a        value for mass distribution RMAvAr between the front and rear of        the vehicle, as a function of the front apparent dynamic mass        MDAAV the rear apparent dynamic mass MDAAR, the front        aerodynamic bias BAAV and the rear aerodynamic bias BAAR.    -   a means for calculating the roll moment of inertia I_(θ) and the        pitch moment of inertia I_(φ) as a function of the sprung mass        MSUS and the rear sprung mass MSUSAR,    -   a means for calculating the distance Ig between the center of        gravity G and the front wheel A, B axle,    -   a means for calculating a heave modal stiffness k_(z), a pitch        modal stiffness k_(φ) and a roll modal stiffness k_(θ) as a        function of the static attitude AS and the front-rear mass        distribution value RMAvAr.

The front apparent dynamic mass MDAAV is calculated by

-   -   calculating the relative front displacement, which is equal to        the mean displacement (half-sum) of the displacements DEB of the        front wheels A, B, to which a front offset constant is then        added,    -   retrieving a spring flexure front dynamic load value EDFAV from        a recorded table or curve that gives this load EDFAV as a        function of front relative displacement,    -   calculating the front apparent dynamic mass MDAAV with the        formula:        MDAAV=(EDFAV·2/g)+front constant,

where g is the gravity acceleration constant=9.81 m/s⁻².

The rear apparent dynamic mass MDAAR is calculated by

-   -   calculating the relative rear displacement, which is equal to        the mean displacement (half-sum) of the displacements DEB of the        rear wheels C, D, to which a rear offset constant is then added,    -   retrieving a spring flexure rear dynamic load value EDFAR from a        table or recorded curve that gives this load EDFAR as a function        of relative rear displacement,    -   calculating the rear apparent dynamic mass MDAAR with the        formula:        MDAAR=(EDFAR·2/g)+rear constant.

The spring flexure dynamic load is zero in the spring's equilibriumposition, corresponding to its static position, with relative frontdisplacement being the displacement with respect to the staticequilibrium position; the value is retrieved by interpolation from thetable, for example, but it can also be obtained from a recorded curve ofEDFAV, EDFAR.

For a hydropneumatic suspension, the mass MDAAR and the mass MDAAV arecalculated using the front static pressure and the rear static pressure.

The front aerodynamic bias BAAV, analogous to a mass in kg, iscalculated with the formula:BAAV=(CAV·VVH ²)/g,

where CAV is a predetermined front aerodynamic coefficient.

The rear aerodynamic bias BAAR, analogous to a mass in kg, is calculatedwith the formula:BAAR=(CAR·VVH ²)/g,

where CAR is a predetermined rear aerodynamic coefficient.

Calculating the Vehicle Sprung Mass MSUS and the Mass Distribution ValueRMAvAr

First a front axle sprung mass MSUSEAV is calculated. In order to dothis, as shown in FIGS. 7 and 8, in stage S1, the sum (front apparentdynamic mass MDAAV+front aerodynamic bias BAAV) is filtered through alow-pass filter PB1 to obtain a filtered front axle sprung massMSUSEAVF.

Then the following is checked:

-   -   in stage S2, whether the vehicle speed VVH is between a preset        low threshold VVH1 and a preset high threshold VVH2,    -   in stage S3, whether the opening panel information unit IO is        “closed” or the vehicle speed VVH is greater than a prescribed        threshold VVH3,    -   in stage S4, whether the difference between the filtered front        axle sprung mass MSUSEAVF(n) and its value MUSSEAVF(n−1)        previously recorded in the memory is high enough (greater in        absolute value than a prescribed difference Δ).

If these conditions are met, the front axle sprung mass MSUSEAV is takento be equal to the filtered front axle sprung mass MSUSEAVF and isrecorded in the memory MEM in step S5 and in the position of the logicswitch COMLOG shown in FIG. 7.

If one, multiple or all of these conditions are not met, the front axlesprung mass MSUSEAV(n) is unchanged and remains equal to the valueMSUSEAV(n−1) previously recorded in the memory MEM, in step S6 and inthe other position of the logic switch COMLOG.

Then in stage S7, a front sprung mass MSUSAV is calculated by filteringthe front axle sprung mass MSUSEAV through a low-pass filter PB2, andoptionally by saturating the values obtained through this filter above ahigh threshold and below a low threshold.

The low-pass filters PB1 and PB2 are first order, for example, each witha cutoff frequency of 0.02 Hz.

The procedure is comparable for calculating the rear axle sprung massMSUSEAR and the rear sprung mass MSUSAR, by replacing MDAAV+BAAV withMDAAR+BAAR and replacing MSUSEAVF with MSUSEARF.

The vehicle sprung mass MSUS is then calculated by adding together thefront sprung mass MSUSAV and the rear sprung mass MSUSARMSUS=MSUSAV+MSUSAR

The front-rear mass distribution value RMAvAr is then calculated bydividing the front sprung mass MSUSAV by the vehicle sprung mass MSUSRMAvAr=MSUSAV/MSUS

Calculating the Moments of Inertia

The roll moment of inertia I_(θ) is calculated as a function of the rearsprung mass MSUSAR using the formulaI _(θ) =A _(y) ·MSUSAR+B _(y)

with MSUSAR=(1−RMAvAr)·MSUS,

where A_(y) and B_(y) are preset parameters.

The pitch moment of inertia I_(φ) is calculated as a function of thesprung mass MSUS using the formulaI _(φ) =A _(x) ·MSUS+B _(x)

where A_(x) and B_(x) are preset parameters.

Calculating the Distance Ig and the Modal Stiffnesses

A front suspension stiffness kAV and a rear suspension stiffness kAr arecalculated.

The front suspension stiffness kAV is obtained by using the prerecordedtable or curve that gives the front suspension stiffness as a functionof the front static attitude to retrieve the front stiffness valuecorresponding to the front static attitude ASav, e.g., using linearinterpolation.

The rear suspension stiffness kAR is obtained by using the prerecordedtable or the curve that gives the rear suspension stiffness as afunction of the rear static attitude to retrieve the rear stiffnessvalue corresponding to the rear static attitude ASar, e.g., using linearinterpolation.

The distance Ig is calculated with the following formula:Ig=(1−RMAvAr)·e

The module CGI in FIG. 4 performs this calculation of the distance Ig,and is part of the estimator 20, for example.

The heave modal stiffness k_(z) is calculated as the sum of the frontsuspension stiffness kAV and the rear suspension stiffness kARk _(z) =kAV+kAR

The pitch modal stiffness d_(φ) is calculated using the formulak _(φ) =kAV·(Ig)² +kAR·(e−Ig)²

The roll modal stiffness k_(θ) is calculated using the formulak _(θ) =Kbadav+Kbadar+v ²·(kAV+kAR)/4

Calculating the Modal Accelerations of the Body

In FIG. 5, a module MLR uses a recorded table or curve that gives aflexure force as a function of the length of the spring R to calculatethe absolute flexure force FLEX-ABS corresponding to the actual inputvalue LR of this length. This recorded curve of flexure force also takesthe suspension stops into account, which are made of rubber, forexample, and which exert a larger force on the body when the spring ispushing on these stops at the damper's AM end of travel.

In addition, a module MDEA receives the static attitude AS as input andfrom the latter, it calculates the corresponding static flexure loadDEAV on the front wheels and the corresponding static flexure load DEARon the back wheels.

From the absolute flexure force FLEX-ABS a subtractor SOUS subtracts thestatic force DEAV or DEAR, i.e., the force DEAV, in the case of thefront wheel A, to obtain a flexure force FLB for suspension springs andstops, corresponding to the force exerted by the spring R and the endstops on the body 2.

An adder AD2 adds the damping force FAM, the dry friction force FSEC,and the flexure force FLB for the springs and the suspension stops toobtain the force FA using the following formula:FA=FAM+FSEC+FLB.

A module CAL-ACC receives as input the torque C_(BAD) calculated by themodule 11, the suspension forces FA, FB, FC, FD calculated by theestimator 12, the mass M of the body, the roll moment of inertia I_(θ)and the pitch moment of inertia I_(φ), which are prerecorded, in orderto calculate the modal accelerations {umlaut over (z)}G, {umlaut over(θ)} and {umlaut over (φ)} as a function therefrom, disregarding theinfluence of the torques C_(θ) and C_(φ), i.e., by having C_(θ)=0 andC_(φ)=0, in one embodiment.

In the improvement described below, the torques C_(θ) and C_(φ) aretaken into account in calculating the modal accelerations.

A module CGI for calculating the inertia magnitude calculates, as afunction of M, I_(θ), I_(φ) and an input value for front-rear massdistribution RMAvAr, a total vehicle mass MTOT=MREF, figuring in astandardized load for the vehicle, e.g., four people weighing 67 kg inthe vehicle passenger compartment, and 28 kg of luggage in the reartrunk, and the distance Ig between the center of gravity G and the frontwheel A, B axle, which is input into the module CAL-ACC. The massdistribution value RMAvAr is continuously estimated using thedisplacement values DEB provided by the displacement sensors CAP-DEB andcomparing each of these values to a calculated mean displacement DEB.

An accelerometer CAP-ACCT is provided on the vehicle in order to supplya transverse acceleration ACCT to a roll torque C_(θ) estimator 14,which also receives as input the total mass MTOT and a transverseacceleration ACCT reset value RECT.

The transverse accelerometer CAP-ACCT is positioned at the center ofgravity G, not at the roll center CR. The transverse acceleration resetvalue RECT is calculated by the module CAL-ACC as follows:RECT(n)=ACCT(n)−{umlaut over (θ)}(n−1)·(HCdG−hRoulis)

where {umlaut over (θ)} is the unfiltered roll acceleration, and

where n indicates the value of the variable in the current cycle and(n−1) indicates the value of the variable in the previous cycle.

The estimator 14 calculates the roll torque C_(θ) using the followingformula:c _(θ)=(ACCT−RECT)·(MTOT)·d(G,CR)

where d(G,CR)=HCdG−hRoulis is the distance between the center of gravityG and the roll center CR, and is prerecorded.

A pitch torque C_(φ) estimator 15 receives as input the distance Ig, thetotal mass MTOT, a longitudinal acceleration ACCL provided by alongitudinal accelerometer CAPL placed in the vehicle body, a brakinginformation unit IF and a longitudinal acceleration reset value RECLcalculated by the module CAL-ACC.

The longitudinal acceleration reset value RECL is calculated by themodule CAL-ACC as follows:RECL(n)=ACCL(n)−{umlaut over (φ)}(n−1)·(HCdG)where {umlaut over (φ)} is the unfiltered pitch acceleration.

The estimator 15 calculates the pitch torque C_(φ) using the followingformula:c _(φ)=(ACCL−RECL)·(MTOT)·h _(G) +c _(φB)

h_(G)=HCdG represents the height of the center of gravity G on the Zaxis with respect to the pitch center CT, and is prerecorded.

The torque c_(φ) component c_(φB) is the component of pitch torque dueto the Brouilhet effect, and is calculated as a function of the brakinginformation unit IF. A determination module 16 provides this brakinginformation unit IF as a function of a master cylinder pressure valueP_(MC), which is itself provided by a brake master cylinder pressuresensor CAP-P.

The calculated values of the torques C_(θ) and C_(φ) are input into themodule CAL-ACC, which uses these values and the other input values toperform calculations and produces heave modal acceleration {umlaut over(z)}G, roll modal acceleration {umlaut over (θ)} and pitch modalacceleration {umlaut over (φ)} as output, as well as the reset valuesRECT and RECL. The roll modal acceleration {umlaut over (θ)} and thepitch modal acceleration {umlaut over (φ)} are respectively sent to twoconverters C1 and C2 of degrees into radians per second, and are thensent with {umlaut over (z)}G to an output SACC for the three unfilteredmodal accelerations, and from there to an output SACC2 from module 10 tothe outside.

In addition, these three modal accelerations at the module 10 outputSACC are each sent to a filter 17 that eliminates the low frequenciesbelow a low cutoff frequency of 0.1 Hz, 0.2 Hz or 0.3 Hz, for example.The filter 17 can have a low-pass component, for example, in addition tothis high-pass component, to form a bandpass filter. The low cutofffrequency of the filter 17 can vary depending on the modal acceleration{umlaut over (z)}G, {umlaut over (θ)} or {umlaut over (φ)}.

The filtered modal accelerations from the output of the filter 17 arethen sent to an integrator module 18 having a high-pass filter at itsoutput, which yields the estimated body modal velocities, namely, thebody heave modal velocity żG, the body roll modal velocity {dot over(θ)}, and the body pitch modal velocity {dot over (φ)} at an output ofmodule 10.

These body heave żG, roll {dot over (θ)} and pitch {dot over (φ)} modalvelocities are absolute velocities with respect to a Galilean referenceframe, and are called first body modal modal velocities for Skyhookcomfort logic.

The computer CSS then calculates the control magnitude ER for the damperAM actuator M for wheel A and for the other wheels B, C, D as a functionof these calculated modal velocities żG, {dot over (θ)} and {dot over(φ)}, and provides the control magnitudes ER thus calculated to thecorresponding actuators M at their control inputs COM.

“Skyhook”-Type Control

Below we describe the calculation of a variable damping modal gainb_(mod) and a first modal setpoint force F_(mod) for the damper forcomfort-based or “Skyhook” damping control.

This Skyhook-type logic uses the first absolute body modalvelocities—heave żG, roll {dot over (θ)} and pitch {dot over(φ)}—produced by the module 10, designated by the general symbol V_(mod)in the following.

Body Movement and Body Bounce Levels

An estimator 24 is provided for calculating a level NMC of body movementand a level NTC of body bounce as a function of the wheel displacementsDEB.

In FIG. 9, the body movement level NMC and the body bounce level NTC areobtained in the estimator 24 by:

-   -   calculating the mean displacement DEBAVMOY for the front wheels        A, B,    -   filtering the front mean displacement DEBAVMOY through a        bandpass filter PB3 to obtain a filtered value |DEBAVMOYF|,    -   taking the absolute value of the filtered value |DEBAVMOYF|, in        a rectifier module RED, to obtain a rectified value |DEBAVMOYF|,    -   keeping the maxima of the rectified value |DEBAVMOYF| in a        maintenance module MMAX, which provides the body movement level        NMC.

For calculating the body movement level NMC, the bandpass filter PB3 isset so that the body movement frequencies, which are relatively low, canpass through. The body movement bandpass filter PB3 is set from 0.5 to2.5 Hz, for example, and is close to the resonant frequency of thesuspension. It can be set between two slopes, for example, to obtain anattenuated movement level NMC and a non-attenuated movement level NMC.

In order to calculate the body bounce level NTC, the bandpass filter PB3is set so that the body bounce frequencies, which are relatively high,can pass through. The body bounce bandpass filter PB3 is set with a lowcutoff frequency of 3 Hz, for example, and a high cutoff frequency of 8Hz or more. It can be set between two slopes, for example, in order toobtain an attenuated bounce level NTC and a non-attenuated bounce levelNTC.

The maintenance module MMAX can have a parameter-adaptive downslope anda parameter-adaptive dwell time for maintaining the maxima. The selecteddwell time for maintaining the maxima is shorter for obtaining the bodybounce level NTC than for obtaining the body movement level NMC.

Skyhook Modal Setpoint Forces and Modal Gains

An estimator 21 is provided for calculating the variable damping modalgains b_(mod) and the first modal damping setpoint forces F_(mod), usingthe formula F_(mod)=−b_(mod)·V_(mod).

There is thus:

-   -   a heave modal gain b_(z) for calculating the first heave modal        force F_(z1)=−b_(z)·żG    -   a roll modal gain b_(θ) for calculating the first roll modal        force F_(θ1)=−b_(θ)·{dot over (θ)}    -   a pitch modal gain b_(φ) for calculating the first pitch modal        force F_(φ1)=−b_(φ)·{dot over (φ)}

The modal gains b_(z), b_(θ), b_(φ) vary as a function of thedisplacements DEB of the wheels A, B, C, D and are calculated by theestimator 21 from the values that were previously calculated as afunction of these wheel A, B, C, D displacements DEB.

The modal gains b_(z), b_(θ), b_(φ) can comprise one or more multipliercoefficients, with the following multiplier coefficients as an example:

-   -   a reference multiplier coefficient b_(zREF), b_(θREF), b_(φREF),        for heave, roll and pitch, respectively    -   an attenuation multiplier coefficient b_(zATT), b_(θATT),        b_(φATT), for heave, roll and pitch,    -   a reset multiplier coefficient b_(zREC), b_(θREC), b_(φREC), for        heave, roll and pitch, respectively,    -   a driving mode multiplier coefficient b_(zTYP), b_(θTYP),        b_(φTYP), for heave, roll and pitch, respectively.

In the embodiment shown in FIG. 6, the estimator 21 receives thefollowing values as input:

-   -   the body movement level NMC provided by the estimator 24,    -   the body bounce level NTC provided by the estimator 24,    -   the vehicle speed VVH,    -   the modal stiffnesses provided by the estimator 24: the heave        stiffness k_(z), the pitch stiffness k_(φ) and the roll        stiffness k_(θ),    -   the modal velocities V_(mod) provided by module 10: the body        heave modal velocity żG, the body roll modal velocity {dot over        (θ)}, the body pitch modal velocity {dot over (φ)},    -   the modal moments of inertia provided by the estimator 20: the        roll moment of inertia I_(θ) and the pitch moment of inertia        I_(φ),    -   the sprung mass MSUS provided by the estimator 20,    -   an information unit IS for sportive mode, which can be in a        Boolean state 0 for non-sportive mode, or in another Boolean        state 1 for sportive mode, according to whether the vehicle        driver has set a corresponding vehicle dashboard button to a        sportive mode position or a non-sportive mode position,        respectively.

For each of the modal gains b_(z), b_(θ), b_(φ), the referencemultiplier coefficient b_(zREF), b_(θREF), b_(φREF), for heave, roll andpitch, respectively, is obtained by using a prerecorded reference tableor curve that gives the reference multiplier coefficient as a functionof the vehicle speed to retrieve the reference multiplier coefficientvalue b_(zREF), b_(θREF), b_(φREF) that corresponds to the vehicle speedinput value VVH, e.g., by linear interpolation.

For each of the modal gains b_(z), b_(θ), b_(φ), the attenuationmultiplier coefficient b_(zATT), b_(θATT), b_(φATT) for heave, roll andpitch, respectively, is obtained.

-   -   by calculating a resistance R_(z), R_(θ), R_(φ), for heave, roll        and pitch, respectively, as a function of the body movement        level NMC and the body bounce level NTC, using the formula:        R _(z) =NTC−β _(z) ·NMC        R _(θ) =NTC−β _(θ) ·NMC        R _(φ) =NTC−β _(φ) ·NMC        where β_(z), β_(θ), β_(φ) are prerecorded parameters that make        it possible to adjust the ratio between the two levels NMC and        NTC, these parameters β_(z), β_(θ), β_(φ) being set between 0.5        and 1, for example;    -   by using a prerecorded table or curve that gives the attenuation        multiplier coefficient b_(zATT), b_(θATT), b_(φATT) as a        function of heave, roll and pitch resistance, respectively, to        retrieve the attenuation multiplier coefficient value b_(zATT),        b_(θATT), b_(φATT) that corresponds to the calculated resistance        value R_(z), R_(θ), R_(φ) for heave, roll and pitch,        respectively, e.g., by linear interpolation.

The attenuation multiplier coefficient b_(zATT), b_(θATT), b_(φATT) forheave, roll and pitch is given, e.g., by the formula:b _(zATT)=1/(1+a _(z) ·R _(z))b _(θATT)=1/(1+a _(θ) ·R _(θ))b _(φATT)=1/(1+a _(φ) ·R _(φ))where a_(z), a_(θ), a_(φ) are prerecorded parameters.

The value obtained b_(zATT), b_(θATT), b_(φATT) is retained only if theassociated resistance R_(z), R_(θ), R_(φ) is greater than a prescribedthreshold, for example. If the associated resistance R_(z), R_(θ), R_(φ)is less than or equal to this prescribed threshold, then 1 is used asthe attenuation multiplier coefficient b_(zATT), b_(θATT), b_(φATT).

For each of the modal gains b_(z), b_(θ), b_(φ), the reset multipliercoefficient b_(zREC), b_(θREC), b_(φREC), for heave, roll and pitch,respectively, is obtained with the formula

$b_{zREC} = \sqrt{\frac{k_{z} \cdot {MSUS}}{k_{zREF} \cdot {MREF}}}$$b_{\theta\;{REC}} = \sqrt{\frac{k_{\theta} \cdot I_{\theta}}{k_{\theta\;{REF}} \cdot I_{\theta\;{REF}}}}$$b_{\varphi\;{REC}} = \sqrt{\frac{k_{\varphi} \cdot I_{\varphi}}{k_{\varphi\;{REF}} \cdot I_{\varphi\;{REF}}}}$where k_(zREF) is a constant, reference heave stiffness,k_(θREF) is a constant, reference roll stiffness,k_(φREF) is a constant, reference pitch stiffness,I_(θREF) is a constant, reference roll moment of inertia,k_(φREF) is a constant, reference pitch moment of inertia,k_(zREF), k_(θREF), k_(φREF), MREF, I_(θREF), I_(φREF) are prerecordedparameters, corresponding to a standardized load for the vehicle, e.g.,four people weighing 67 kg in the vehicle passenger compartment, and 28kg of luggage in the rear trunk.

For each of the modal gains b_(z), b_(θ), b_(φ), the driving modemultiplier coefficient b_(zTYP), b_(θTYP), b_(φTYP), for heave, roll andpitch, respectively, is equal to a prerecorded sportive mode gainGS_(z), GS_(θ), GS_(φ), if the sportive mode information unit IS is inthe sportive mode Boolean state 1, and is equal to 1 if the sportivemode information unit IS is in the non-sportive mode Boolean state 0.

The modal gains b_(z), b_(θ), b_(φ) are calculated using the multipliercoefficients with the formulas:b _(z) =b _(zREF) ·b _(zATT) ·b _(zREC) ·b _(zTYP)b _(θ) =b _(θREF) ·b _(θATT) ·b _(θREC) ·b _(θTYP)b _(φ) =b _(φREF) ·b _(φATT) ·b _(φREC) ·b _(φTYP)The first heave modal force F_(z1), the first roll modal force F_(θ1),and the first pitch modal force F_(φ1) are calculated, and are alsocalled comfort or “Skyhook” modal forces. The first heave modal forceF_(z1), the first roll modal force F_(θ1), and the first pitch modalforce F_(φ1) are provided at an output of the estimator 21.

Roadhook Logic

Below we describe the Roadhook-type logic, i.e., a logic that followsthe road profile; this logic is also known as body attitude logic orhandling logic.

The principle of this body attitude logic is to minimize or to make tendtoward zero one or more of the modal body accelerations—heave, roll andpitch acceleration—with respect to the plane of the wheels.

In FIG. 10, the device has an estimator 31 for body modal velocitiesV_(mod2) with respect to the mid-plane of the wheels as a function ofthe measured displacements DEB of the wheels A, B, C, D. These modalvelocities V_(mod2) with respect to the mid-plane of the wheels arecalled relative velocities, and they include the relative body heavevelocity ż_(G2), the relative body pitch velocity {dot over (φ)}₂, andthe relative body roll velocity {dot over (θ)}₂.

This estimator 31 of relative modal velocities V_(mod2) receives asinput:

-   -   the displacements DEB measured on the wheels A, B, C, D.    -   the track width v,    -   at least two of the following parameters: the front-rear mass        distribution value RMAvAr, the distance Ig between the center of        gravity G and the front wheel A, B axle, and the wheelbase e.

First the displacements DEB are filtered through a low-pass filter,e.g., a second-order Butterworth-type filter, to obtain only thelow-frequency displacements and to substantially eliminatehigh-frequency bouncing.

Then a derivation circuit derives the displacements DEB thus filtered inorder to obtain the wheel A, B, C, D Roadhook displacement velocities.

The relative modal velocities V_(mod2) are then calculated using thefollowing formulas:

-   -   relative body heave modal velocity with respect to the mid-plane        of the wheels:

${\overset{.}{z}}_{G\; 2} = {{\frac{\left( {e - \lg} \right)}{e}\frac{{\overset{.}{d}}_{A} + {\overset{.}{d}}_{B}}{2}} + {\frac{\lg}{e}\frac{{\overset{.}{d}}_{C} + {\overset{.}{d}}_{D}}{2}}}$

-   -   relative body pitch modal velocity with respect to the mid-plane        of the wheels:

${\overset{.}{\varphi}}_{2} = \frac{{\overset{.}{d}}_{A} - {\overset{.}{d}}_{B} - {\overset{.}{d}}_{C} + {\overset{.}{d}}_{D}}{2\; e}$

-   -   relative body roll modal velocity with respect to the mid-plane        of the wheels:

${\overset{.}{\theta}}_{2} = \frac{{\overset{.}{d}}_{A} - {\overset{.}{d}}_{B} - {\overset{.}{d}}_{C} + {\overset{.}{d}}_{D}}{2\; v}$with{dot over (d)}_(A)=displacement speed VDEB for the left front wheel A,{dot over (d)}_(B)=displacement speed VDEB for the right front wheel B,{dot over (d)}_(C)=displacement speed VDEB for the right rear wheel C,{dot over (d)}_(D)=displacement speed VDEB for the left rear wheel D.

Anticipated Transverse Jerk

An estimator 32 is provided to calculate an anticipated transverse jerk

(third derivative of the Y-coordinate with respect to time) from themeasured vehicle speed VVH and the rotation speed {dot over (δ)} of thevehicle steering wheel, where 6 is the measured angle of rotation ofthis steering wheel, as measured by any appropriate sensor or means.

This estimator 32 receives as input:

-   -   the sprung mass MSUS,    -   the front-rear mass distribution value RMAvAr,    -   the vehicle speed VVH,    -   the rotation speed {dot over (δ)} of the steering wheel.

Anticipated transverse jerk

is estimated using the formula:

$= \frac{D \cdot \overset{.}{\delta} \cdot {VVH}^{2}}{e\left( {1 + {K \cdot {VVH}^{2}}} \right)}$

where D is the gear reduction of the steering wheel and K is anoversteer gain constant, calculated from the front-rear massdistribution value RMAvAr and the sprung mass MSUS. The oversteer gain Kis a vehicle value, determined from measurements performed on thevehicle.

Anticipated Engine Torque to the Wheels

An estimator 40 is provided for calculating this anticipated enginetorque to the wheels, designated as C_(R).

In order to do this, the number i of the engaged gear R_(EMBR)(i) of thevehicle gearbox is estimated, in a range from 1 to 5, for example.

The speed VVH1 the vehicle would be going at a prescribed enginerotation speed ω_(MOT1), which, in an engaged position, depends only onthe gear R_(EMBR) engaged, is calculated according to the formulaVVH1=VVH·ΩMOT1/ΩMOTwhere Ω_(MOT) is the engine rotation speed at the vehicle speed VVH. Forexample, Ω_(MOT1)=1000 rpm.

For each gear ratio i, the following parameters are calculated:P _(i)=0.5·(VVH1(i)+VVH1(i+1)).

By comparing VVH1 to P_(i) and by retaining the value of P_(i) closestto VVH1, the gear ratio I is obtained.

The anticipated engine torque C_(R) to the wheels is then:C _(R) =C _(M) ·R _(EMBR)(i),

with R_(EMBR)(i)=ω_(MOT)/ω_(ROUE)

where R_(EMBR)(i) is the gear ratio having the number i,

C_(M) is the engine torque, determined by any appropriate means, e.g. anengine control computer.

ω_(ROUE) is the wheel rotation speed.

Anticipated Longitudinal Jerk

An estimator 33 is provided for calculating an anticipated longitudinaljerk

(third derivative of the X-coordinate with respect to time) from thederivative of the anticipated engine torque and the derivative {dot over(P)}_(MC) of the master cylinder pressure P_(MC).

This estimator 33 receives as input:

-   -   the sprung mass MSUS,    -   the master cylinder pressure P_(MC),    -   the anticipated engine torque to the wheels C_(R).

The calculation is performed as follows.

First, a prerecorded curve or table that gives a braking force for themaster cylinder as a function of the master cylinder pressure is used toretrieve the value EFR of this braking force that corresponds to themaster cylinder pressure P_(MC), e.g., by linear interpolation. Next, alow-pass filter is applied to this breaking force EFR, e.g. afirst-order Butterworth-type filter, and the braking force EFR thusfiltered is derived in a derivation circuit in order to obtain thederivative Ė_(FRF) of the filtered force EFR.

An anticipated engine force to the wheels EMR, equal to the anticipatedengine torque to the wheels C_(R) divided by a predetermined andprerecorded mean wheel radius Rmoy, is calculated. Next, a low-passfilter is applied to this anticipated engine force to the wheels EMR,e.g. a first-order Butterworth-type filter, and the anticipated engineforce EMR thus filtered is derived in a derivation circuit in order toobtain the derivative Ė_(MRF) of the filtered force EMR.

The anticipated longitudinal jerk

is then equal to the sum of the derivatives Ė_(FRF), Ė_(MRF), divided bythe total mass MTOT:

$= \frac{{\overset{.}{E}}_{FRF} + {\overset{.}{E}}_{MRF}}{MTOT}$

In this formula, the total mass MTOT includes the sprung mass MSUS, itcan include the mass of the wheels, and can be limited between twothresholds.

These jerks

and

are estimated and do not come from a derivation of accelerometers, whichare too noisy and too late.

Anticipatory Modal Force Terms

A module 34 is provided for calculating anticipatory modal force terms,namely:

an anticipatory pitch modal torque, designated by c_(φ2ant),

an anticipatory roll modal torque, designated by c_(θ2ant).

No anticipatory heave modal force is calculated, given that only onecorrective Roadhook modal force is used for heave, as will be describedbelow.

In the embodiment shown in FIG. 11, the estimator 34 receives thefollowing values as input:

-   -   the anticipated transverse jerk        provided by the estimator 32,    -   the anticipated longitudinal jerk        provided by the estimator 33,    -   the vehicle speed VVH,    -   the modal stiffnesses provided by the estimator 24: the heave        modal stiffness k_(z), the pitch modal stiffness k_(φ) and the        roll modal stiffness k_(θ),    -   the relative modal velocities V_(mod2) with respect to the        mid-plane of the wheels, provided by the module 31: relative        body heave modal velocity ż_(G2), relative body roll modal        velocity {dot over (θ)}₂, relative body pitch modal velocity        {dot over (φ)}₂,    -   the modal moments of inertia provided by the estimator 20: the        roll moment of inertia I_(θ) and the pitch moment of inertia I,    -   the sprung mass MSUS provided by the estimator 20,    -   the sportive mode information unit IS.

As shown in FIG. 11, each of these anticipatory modal force terms forpitch c_(φ2ant) and roll c_(θ2ant) is calculated by respectivelyprocessing the anticipated longitudinal jerk

and the anticipated transverse jerk

to obtain a processed anticipated longitudinal jerk

_(T), and a processed anticipated transverse jerk

_(T), then multiplying by a longitudinal stress gain G_(SX) to obtainthe anticipatory pitch torque c_(φ2ant) and by a transverse stress gainG_(SY) to obtain the anticipatory roll torque C_(θ2ant) using theformulas:c _(φ2ant) =G _(SX)·

_(T)c _(θ2ant) =G _(SY)·

_(T)

The longitudinal stress gain G_(SX) and the transverse stress gainG_(SY) are predetermined adjustment parameters, determined by vehicletesting in order to obtain the proper body attitude responses to thedriver's demand.

This formulation is described below for calculating the anticipatorypitch torque, designated by c_(φ2ant), from the anticipated longitudinaljerk

:

-   -   the anticipated longitudinal jerk        passes through a low-amplitude canceling filter 341 having a        high positive activation threshold SHJL for longitudinal jerk,        and a low negative activation threshold SBJL for longitudinal        jerk, in order to substitute zero values for the anticipated        longitudinal jerk values        located between the high activation threshold for longitudinal        jerk SHJL and the low activation threshold for longitudinal jerk        SBJL over time;    -   the filtered anticipated longitudinal jerk        from the filter 341 is put through a module 342 for maintaining        maxima that can have a parameter-adaptive dwell time for        maintaining maxima, in order to obtain a jerk that is filtered        and kept at its maxima, designated by        _(f max),    -   the jerk        _(f max) from module 342, filtered and maintained at its maxima,        is put through a slope-limiting module 343 that limits the        absolute value of the downslope of the jerk        _(f max), filtered and maintained at its maxima, so as to obtain        the processed anticipated longitudinal jerk        , which is then multiplied respectively by the longitudinal        stress gain G_(SX) to obtain the anticipatory pitch torque        c_(φ2ant).

The dwell time must be long enough so that the corrective Roadhook term(see supra) has time to become significant for a simple action (simplecornering, braking or accelerating) and short enough so as not todisturb Roadhook operation and not to require needless damping.

When the anticipated transverse jerk

is put into the canceling filter 341, which has its high positiveactivation threshold SHJT for transverse jerk and its low negativeactivation threshold SBJT for transverse jerk, and then into the module342 for maintaining maxima, this produces a jerk that is filtered andmaintained at its maxima, designated as

_(f max), which is sent to the slope-limiting module 343 that has thetransverse stress gain G_(SY), in order to produce as output theanticipatory roll modal torque c_(θ2ant). The high thresholds SHJT andSHJL can be equal and opposite to the equal low thresholds SBJT andSBJL. These thresholds are parameter-adaptive and are a trade-offbetween limiting ill-timed actions and ignoring small demands.Preferably, each of the thresholds SHJT, SHJL, SBJT and SBJL is between1 and 10 ms⁻³.

The use of anticipatory terms makes it possible to improve response timein order to set the actuators in the right state before the body has hadtime to pick up speed. This results in a notable improvement in bodyattitude.

Corrective Modal Force Terms

The module 34 also calculates at least one second corrective modal forceterm F_(2COR) as a function of relative modal velocity V_(mod2)=ż_(G2),{dot over (φ)}₂, {dot over (θ)}₂ with respect to the mid-plane of thewheels, using the general formulaF _(2COR) =−b _(mod2) ·V _(mod2)

namely:

-   -   a second corrective heave modal force, designated as F_(z2cor),    -   a second corrective pitch modal torque, designated as C_(φ2cor),    -   a second corrective roll modal torque, designated as c_(θ2cor),        using the formulas:        F _(z2cor) =−b _(z2) ·ż _(G2)        c _(φ2cor) =−b _(φ2)·{dot over (φ)}₂        F _(θ2cor) =−b _(θ2)·{dot over (θ)}₂

where b_(mod2) is a second corrective modal gain,

b_(z2) is a second corrective heave modal gain for calculating thesecond corrective heave modal force F_(z2cor),

b_(θ2) is a second corrective roll modal gain for calculating the secondcorrective roll modal torque c_(θ2cor),

b_(φ2) is a second corrective pitch modal gain for calculating thesecond corrective pitch modal torque c_(φ2cor).

The second corrective modal gains b_(z2), b_(θ2), b_(φ2) can include oneor more multiplier coefficients, e.g., with the following multipliercoefficients:

-   -   a second reference multiplier coefficient b_(zREF2), b_(θREF2),        b_(φREF2), for heave, roll and pitch, respectively,    -   a second reset multiplier coefficient b_(zREC2), b_(θREC2),        b_(φREC2), for heave, roll and pitch, respectively,    -   a second driving mode multiplier coefficient b_(zTYP2),        b_(θTYP2), b_(φTYP2), for heave, roll and pitch, respectively.

For each of the second modal gains b_(z2), b_(θ2), b_(φ2), the secondreference multiplier coefficient b_(zREF2), b_(θREF2), b_(φREF2), forheave, roll and pitch, respectively, is obtained by using a secondprerecorded reference curve or table for Roadhook logic that gives thesecond reference multiplier coefficient as a function of the vehiclespeed to retrieve the second reference multiplier coefficient valueb_(zREF2), b_(θREF2), b_(φREF2) that corresponds to the vehicle speedVVH input value, e.g., by linear interpolation.

For each of the second modal gains b_(z2), b_(θ2), b_(φ2), the secondreset multiplier coefficient b_(zREC2), b_(θREC2), b_(φREC2) is, forexample, equal to the first reset multiplier coefficient b_(zREC),b_(θREC), b_(φREC) for heave, roll and pitch, respectively, describedabove: b_(zREC2)=b_(zREC), b_(θREC2)=b_(θREC), b_(φREC2)=b_(φREC).

For each of the second modal gains b_(z), b_(θ), b_(φ), the seconddriving mode multiplier coefficient b_(zTYP2), b_(θTYP2), b_(φTYP2), forheave, roll and pitch, respectively, is, for example, equal to the firstdriving mode multiplier coefficient b_(zTYP), b_(θTYP), b_(φTYP),described above:b _(zTYP2) =b _(zTYP) ,b _(θTYP2) =b _(θTYP) ,b _(φTYP2) =b _(φTYP).

The second corrective modal gains b_(z2), b_(θ2), b_(φ2) are calculatedfrom the second multiplier coefficients, using the formulas:b _(z2) =b _(zREF2) ·b _(zREC2) ·b _(zTYP2)b _(θ2) =b _(θREF2) ·b _(θREC2) ·b _(θTYP2)b _(φ2) =b _(φREF2) ·b _(φREC2) ·b _(φTYP2)

Roadhook Modal Forces

Next, the estimator 34 brings together

-   -   the anticipatory pitch modal torque c_(φ2ant) and the second        corrective pitch modal torque c_(φ2cor) to obtain as output the        second pitch force or torque c_(φ2),    -   the anticipatory roll modal torque c_(θ2ant) and the second        corrective roll modal torque c_(θ2cor) to obtain as output the        second roll torque or force c_(θ2).

The second corrective heave modal force, designated as F_(z2cor) istaken as the output for the second heave modal force F_(z2)=F_(z2cor).

These second forces c_(φ2), c_(θ2) and F_(z2) are called handling orroad-holding or “Roadhook” modal forces.

The output is obtained by choosing the anticipatory term or thecorrective term, depending on their values, as shown in the table below.

Corrective Anticipatory Term Term Small Large Small Case 1: CorrectiveTerm Case 3: Anticipatory Term Large Case 2: Corrective Term Case 4: Thelarger of the 2, if same sign Corrective term if opposite signs

To obtain the second pitch modal force c_(φ2), the latter is equal to

-   -   the second corrective pitch modal torque c_(φ2cor), when the        absolute value of the anticipatory pitch torque c_(φ2ant) is        less than or equal to a first prescribed pitch value V1φ, (case        1 and 2 in the table, corresponding to the small anticipatory        term),    -   the anticipatory pitch modal torque c_(φ2ant), when the absolute        value of the anticipatory pitch torque c_(φ2ant) is greater than        the first prescribed pitch value V1φ, and when the absolute        value of the corrective pitch torque c_(φ2cor) is less than or        equal to a second prescribed pitch value V2φ (case 3 in the        table, corresponding to the small corrective term and the large        anticipatory term).

If the absolute value of the anticipatory pitch torque c_(φ2ant) isgreater than the first prescribed pitch value V1φ and if the absolutevalue of the corrective pitch modal torque c_(φ2cor) is greater than thesecond prescribed pitch value V2φ (case 4 in the table, corresponding tothe large corrective term and the large anticipatory term), then

-   -   if the corrective pitch modal torque c_(φ2cor) and the        anticipatory pitch torque c_(φ2ant) have the same sign, the        second pitch modal force c_(φ2) is equal to max(|c_(φ2cor)|,        |c_(φ2ant)|)·sgn(c_(φ2ant)),        where sgn designates the sign function and max designates the        maximum function, and    -   if the corrective pitch modal torque c_(φ2cor) and the        anticipatory pitch torque c_(φ2ant) do not have the same sign,        the second pitch modal force c_(φ2) is equal to the corrective        pitch torque c_(φ2cor).

Obtaining the second roll force c_(θ2) is comparable to the aboveprocedure, using c_(θ2cor) and c_(θ2ant) instead of c_(φ2cor) andc_(φ2ant), with a first prescribed roll value V1θ instead of V1φ, and asecond prescribed roll value V2θ instead of V2φ.

Combining Skyhook and Roadhook

The first heave modal force F_(z1), the first roll modal force F_(θ1)and the first pitch modal force F_(φ1) provided by the estimator 21(comfort modal forces in Skyhook logic, generally designated as firstmodal setpoint forces F1), as well as the second heave modal forceF_(z2), the second roll modal force c_(θ2) and the second pitch modalforce c_(φ2) provided by the estimator 34 (handling modal forces inRoadhook logic, generally designated as second modal setpoint forcesF2), are sent to a setpoint force estimator 22 for each damper, thus forthe wheels A, B, C, D, the setpoint forces FA1, FB1, FC1, FD1.

For each mode, the estimator 22 weights the first comfort force F1 andthe second handling force F2 in order to calculate the modal setpointforce F.

The estimator 22 calculates:

-   -   a heave modal force F=F_(z) setpoint as a function of the first        heave force F_(z1) for comfort, the second heave force F_(z2)        for handling and a weighting coefficient α, using the formula:        F _(z) =α·F _(z2)+(1−α)·F _(z1)    -   a pitch modal force F=F_(φ) setpoint as a function of the first        pitch force F_(φ1) for comfort, the second pitch force c_(φ2)        for handling and the weighting coefficient α, using the formula:        F _(φ) =α·c _(φ2)+(1−α)·F _(φ1)        a roll modal force F=F_(θ) setpoint as a function the first roll        force F_(θ1) for comfort, the second roll force c_(θ2) for        handling and the weighting coefficient α, using the formula:        F _(θ) =α·c _(θ2)+(1−α)·F _(θ1)

The calculation of this weighting coefficient α from detected demands isdescribed below.

The weighting coefficient is normally 0, to cause the first modal forcesetpoints to follow the first comfort forces F_(z1), F_(θ1) and F_(φ1)of Skyhook logic.

Corrected Longitudinal Acceleration

The corrected longitudinal acceleration {umlaut over (X)}_(COR) iscalculated by an estimator 25 from the measured longitudinalacceleration ACCL, provided by the longitudinal accelerometer CAPL.

The estimator 25 receives as input:

-   -   the measured vehicle speed VVH,    -   the sprung mass MSUS provided by the estimator 20,    -   the measured longitudinal acceleration ACCL,    -   the brake master cylinder pressure P_(MC), provided by the        sensor CAP-P,    -   the anticipated engine torque to the wheels C_(R), provided by        the estimator 40.

The calculation is performed as follows.

First the prerecorded table or curve that gives the braking force forthe master cylinder as a function of the master cylinder pressure isused to retrieve the value EFR of this breaking force that correspondsto the master cylinder pressure P_(MC), e.g., using linearinterpolation.

The anticipated engine force to the wheels EMR, which is equal to theanticipated engine torque to the wheels C_(R) divided by a predeterminedand prerecorded mean wheel radius Rmoy, is calculated.

A longitudinal drag force ETR is calculated as a function of the vehiclespeed VVH using the formula:ETR=COEF·(VVH)² +DEC

where COEF is a predetermined, prerecorded coefficient and DEC is apredetermined, prerecorded offset.

The total longitudinal force ELT is equal to the sum of the brakingforce EFR, the anticipated engine force EMR to the wheels and thelongitudinal drag force ETR:ELT=EFR+EMR+ETR

The total mass MTOT, which includes the sprung mass MSUS, can includethe mass of the wheels, and can be limited between two thresholds, iscalculated.

The anticipated longitudinal acceleration {umlaut over (X)}_(ANT) iscalculated by dividing the total longitudinal force ELT by the totalmass MTOT:{umlaut over (X)} _(ANT) =ELT/MTOT

The anticipated longitudinal acceleration {umlaut over (X)}_(ANT) isthen optionally limited between two thresholds.

The corrected longitudinal acceleration {umlaut over (X)}_(COR) is thencalculated by

-   -   calculating a change EVAL in longitudinal acceleration, equal to        the anticipated longitudinal acceleration {umlaut over        (X)}_(ANT) minus the measured longitudinal acceleration ACCL:        EVAL={umlaut over (X)} _(ANT) −ACCL    -   applying a high-pass filter PH, e.g., a first-order        Butterworth-type filter, to this change EVAL in longitudinal        acceleration to obtain the filtered longitudinal change EVAL,        equal to PH({umlaut over (X)}_(ANT)−ACCL),    -   adding the filtered longitudinal change EVAL to the measured        longitudinal acceleration ACCL to obtain the corrected        longitudinal acceleration {umlaut over (X)}_(COR):        {umlaut over (X)} _(COR) =ACCL+PH({umlaut over (X)} _(ANT)        −ACCL)

The cutoff frequency of the high pass filter PH makes it possible toadjust the measurement estimation reset speed.

Corrected Transverse Acceleration

The corrected transverse acceleration Ÿ_(COR) is calculated by anestimator 26 from the measured transverse acceleration ACCT, provided bythe transverse accelerometer CAP-ACCT.

The estimator 26 receives as input:

-   -   the sprung mass MSUS,    -   the front-rear mass distribution value RMAvAr,    -   the vehicle speed VVH,    -   the angle of rotation δ of the steering wheel,    -   the measured transverse acceleration ACCT.

The anticipated transverse acceleration Ÿ_(ANT) is estimated using theformula:

${\overset{¨}{Y}}_{ANT} = \frac{D \cdot \delta \cdot {VVH}^{2}}{e\left( {1 + {K \cdot {VVH}^{2}}} \right)}$

where D is the gear reduction of the steering wheel and K is theoversteer gain constant, calculated as a function of the front-rear massdistribution value RMAvAr and the sprung mass MSUS. The oversteer gainconstant K is a vehicle value, determined from measurements on thevehicle.

The anticipated longitudinal acceleration Ÿ_(ANT) is then optionallylimited between two thresholds.

The corrected longitudinal acceleration Ÿ_(COR) is then calculated by

-   -   calculating a change EVAT in transverse acceleration, equal to        the anticipated transverse acceleration Ÿ_(ANT) minus the        measured transverse acceleration ACCT:        EVAT=Ÿ _(ANT) −ACCT    -   applying a high-pass filter PH2, e.g., a first-order        Butterworth-type filter, to this change EVAT in transverse        acceleration to obtain the filtered transverse change EVAL,        equal to PH Ÿ_(ANT)−ACCT),    -   adding the filtered transverse change EVAT to the measured        transverse acceleration ACCT in order to obtain the corrected        transverse acceleration Ÿ_(COR):        Ÿ _(COR) =ACCT+PH2(Ÿ _(ANT) −ACCT)

The cutoff frequency of the high-pass filter PH2 makes it possible toadjust the measurement estimation reset speed.

Demand Detection and Weighting Coefficient for Skyhook and RoadhookForces

In FIG. 12, an estimator 23 calculates the weighting coefficient α forthe first comfort forces and the second handling forces.

the estimator 23 receives as input:

-   -   the anticipated longitudinal jerk        , provided by the estimator 33,    -   the anticipated transverse jerk        , provided by the estimator 32,    -   the corrected longitudinal acceleration {umlaut over (X)}_(COR),        provided by the estimator 25,    -   the corrected transverse acceleration Ÿ_(COR), provided by the        estimator 26,    -   the sportive mode information unit IS.

By default, the first Skyhook logic comfort forces F_(z1), F_(θ1) andF_(φ1) are selected for the modal setpoint forces, meaning that theweighting coefficient α is 0. The demands are detected from the valuestaken by these inputs. As soon as a demand is detected, the weightingcoefficient α changes to “all handling” or Roadhook—meaning to 1—inorder to select the second handling forces F_(z2), c_(θ2) and c_(φ2) asmodal setpoint forces. If a stabilization is detected during a demand,typically a wide highway curve as in FIG. 14, it is possible to make theweighting coefficient α change progressively to 0 in Skyhook logic so asto give priority to comfort. If a variation in accelerometer values isdetected during this stabilization, the apportionment changesimmediately back to “all handling”, i.e., 1.

A Boolean signal “lateral driver demand” (SSOLT) is created and aBoolean signal “longitudinal driver demand” (SSOLL) when parameter-basedthresholds for corrected acceleration or anticipated jerk are crossed.

The weighting coefficient changes to 1 and the dwell time isreinitialized when the following events are detected:

-   -   rising edge for longitudinal driver demand,    -   rising edge for lateral driver demand,    -   longitudinal jerk crossing the threshold upon longitudinal        driver demand,    -   longitudinal acceleration variation crossing the threshold upon        longitudinal driver demand,    -   transverse jerk crossing the threshold upon transverse driver        demand,    -   transverse acceleration variation crossing the threshold upon        transverse driver demand.

The estimator 23 determines a longitudinal threshold modulation MODL anda transverse threshold modulation MODT as a function of the sportivemode information unit IS.

If the sportive mode information unit IS is equal to 1, the longitudinalthreshold modulation MODL is equal to a prescribed longitudinal valueless than 1 and the transverse threshold modulation MODT is equal to aprescribed transverse value less than 1.

If the sportive mode information unit IS is equal to 0, the longitudinalthreshold modulation MODL is equal to 1 and the transverse thresholdmodulation MOD1 is equal to 1.

Next, demand detection signals are determined: a longitudinal demandlogic signal SSOLL, a second longitudinal logic signal SL2, a thirdlongitudinal logic signal SL3, a transverse demand logic signal SSOLT, afourth transverse logic signal ST4 and a fifth transverse logic signalST5, as follows:if |{umlaut over (X)} _(COR) |>THAL ₁ ·MODLor|

|>THJL ₁ ·MODL

then SSOLL=1,

-   -   otherwise SSOLL=0.        if SSOLL=1 and |        |>THJL ₂

then SL2=1,

-   -   otherwise SL2=0.    -   the longitudinal acceleration γ_(L) is initialized at 0.        if |{umlaut over (X)} _(COR)−γ_(L) |>THAL ₂·|γ_(L)|

then

-   -   γ_(L)={umlaut over (X)}_(COR) is recorded for the next        calculation of SL3,    -   if SSOLL=1 then SL3=1 and otherwise SL3=0,        if |{umlaut over (X)} _(COR)−γ_(L) |≦THAL ₂·|γ_(L)| then SL3=0.        if |Ÿ _(COR) |>THAT ₁ ·MODT        or        |        |>THJT ₁ ·MODT

then SSOLT=1,

-   -   otherwise SSOLT=0.        if SSOLT=1 and |        |>THJT ₂

then ST4=1,

-   -   otherwise ST4=0.    -   the transverse acceleration γ_(T) is initialized at 0.        if |Ÿ _(COR)−γ_(T) |>THAT ₂·|γ_(T)|

then

-   -   γ_(T)=Ÿ_(COR) is recorded for the next calculation of ST5,    -   if SSOLT=1 then ST5=1 and otherwise ST5=0,        if |Ÿ _(COR)−γ_(T) |<THAT ₂·|γ_(T)| then ST5=0.        THAL₁ is a first longitudinal acceleration threshold,        THAL₂ is a second longitudinal acceleration change threshold,        THJL₁ and THJL₂ are first and second longitudinal jerk        thresholds,        THAT₁ is a first transverse acceleration threshold,        THAT₂ is a second transverse acceleration change threshold,        THJT₁ and THJT₂ are first and second transverse jerk thresholds,        these thresholds being prerecorded.

The states 1 of the detection signals correspond to states where ademand is present, and the states 0 correspond to states where there isno demand.

A logic signal SSOL for driver demand is determined to be equal to 1 ifthe first longitudinal demand logic signal SSOLL is 1 and/or if thetransverse demand logic signal SSOLT is 1 (non-exclusive logicaloperator OR).

A first logic signal SL1 is made equal to the driver demand logic signalSSOL.

Based on the sportive mode information unit IS, a modulation time TMODbetween the first Skyhook forces and the second Roadhook forces isdetermined:

-   -   if IS=1 then the modulation time TMOD is equal to        TMOD=TPER·MODSPORT,    -   otherwise TMOD=TPER,        where TPER is a predetermined, prerecorded permanent operating        time that represents the changeover time from Roadhook logic to        Skyhook logic during steady-state operation, and MODSPORT is a        modulation time multiplier factor for sport mode that is greater        than 1 and is predetermined and prerecorded.

In FIG. 13, which shows timing diagrams as a function of time t, anintermediate weighting coefficient α_(INTER) is next calculated asfollows:

-   -   initialization at 0 (stage S10)    -   intermediate weighting coefficient α_(INTER) set at 1 on each        rising edge detected for any or all of the first, second, third,        fourth and fifth logic signals SL1=SSOL, SL2, SL3, ST4, ST5        (stage S11),    -   intermediate weighting coefficient α_(INTER) kept at 1 for a        predetermined, prerecorded dead time TMORT after each of these        detected rising edges (stage S12),    -   intermediate weighting coefficient α_(INTER) reduced to 0, e.g.,        linearly, during the modulation time TMOD after this dead time        TMORT (stage S13),    -   if a new rising edge is detected, the intermediate weighting        coefficient α_(INTER) is reset to 1 following stage S11, and the        process S11, S12, S13 described above is started again.

A limited logic signal SSOL_(LIMIT) for driver demand is calculated byfiltering the driver demand logic signal SSOL through a negative pitchlimiter so that it changes from 1 to 0 minimum in the modulation timeTMOD.

The weighting coefficient α is equal to the intermediate weightingcoefficientα_(INTER) multiplied by the limited logic signal SSOL_(LIMIT)for driver demand:α=α_(INTER) ·SSOL _(LIMIT)

FIG. 14 shows the timing diagrams of the steering wheel angle δ duringsimple cornering, which causes the weighting coefficient α to change to1 (Roadhook) at the beginning and at the end of the turn, while theweighting coefficient α is 0 (Skyhook) before the turn, after the turnand in the middle of the turn.

Setpoint Forces to the Wheels

The prerecorded table or curve that gives the distribution coefficientfor force to the front as a function of the front-rear mass distributionvalue is used to retrieve the value of the front force distributioncoefficient CAV that corresponds to the front-rear mass distributionvalue RMAvAr, e.g., by a linear interpolation. This front forcedistribution coefficient CAV is greater than or equal to 0 and less thanor equal to 1.

An anti-roll ratio RAD greater than or equal to 0 and less than or equalto 1 is calculated as a function of the vehicle speed VVH. For example,the prerecorded table or curve that gives the anti-roll ratio as afunction of the vehicle speed is used to retrieve the anti-roll ratiovalue RAD that corresponds to the vehicle speed VVH, e.g., by linearinterpolation.

The estimator 22 calculates the setpoint forces for the dampers AM onthe wheels A, B, C, D from the modal setpoint forces F_(z), F_(θ) andF_(φ), using the following formulas:

-   -   the setpoint force FA1 for the left front wheel A:

${{FA}\; 1} = {\frac{F_{z} \cdot {CAV}}{2} - \frac{F_{\varphi}}{2 \cdot e} - \frac{F_{\theta} \cdot {RAD}}{v}}$

-   -   the setpoint force FB1 for the right front wheel B:

${{FB}\; 1} = {\frac{F_{z} \cdot {CAV}}{2} - \frac{F_{\varphi}}{2 \cdot e} + \frac{F_{\theta} \cdot {RAD}}{v}}$

-   -   the setpoint force FC1 for the right rear wheel C:

${{FC}\; 1} = {\frac{F_{z} \cdot \left( {1 - {CAV}} \right)}{2} + \frac{F_{\varphi}}{2 \cdot e} + \frac{F_{\theta} \cdot \left( {1 - {RAD}} \right)}{v}}$

-   -   the setpoint force FD1 for the left rear wheel D:

${{FD}\; 1} = {\frac{F_{z} \cdot \left( {1 - {CAV}} \right)}{2} + \frac{F_{\varphi}}{2 \cdot e} - \frac{F_{\theta} \cdot \left( {1 - {RAD}} \right)}{v}}$

From the setpoint forces FA1, FB1, FC1, FD1 for the dampers on thewheels A, B, C, D and from the displacement velocities VDEB valid forthese wheels A, B, C, D, respectively, the estimator then determines thedamping setpoint law ER_(C)=ER_(CA), ER_(CB), ER_(CC), ER_(CD) that mustbe used by the damper AM for the wheel A, B, C, D, e.g., by positioningthe point (VDEB(A); FA1) on the chart in FIG. 15 and looking for theclosest damping law ER.

Minimum States

An estimator 27 calculates minimum damping states. This function makesit possible to keep the suspension out of damping states that are toosoft by imposing minimum states ER_(M), i.e., minimum damping lawsER_(M), as a function of four different input streams:

-   -   the vehicle speed, in order to obtain the first minimum state        ER_(M1): this criteria is used for scenarios in which the        vehicle is at a stop or a very low speed (e.g., going down        sidewalks), or at a very high speed, for safety and body        stability.    -   the corrected longitudinal acceleration, in order to obtain the        second minimum state ER_(M2): this criteria is used for safety        during very high longitudinal demand in cases where Roadhook        logic would not be adequate, and for stabilized acceleration or        braking situations, as opposed to transitory longitudinal        phases.    -   the corrected transverse acceleration, in order to obtain the        third minimum state ER_(M3): this criteria is used for safety        during very high lateral demand in cases where Roadhook logic        would not be adequate, and for stabilized cornering situations,        during which the integration logic gives priority to Skyhook        logic.    -   the anticipated transverse jerk, in order to obtain the fourth        minimum state ER_(M4): this criteria works in parallel with        Roadhook logic using anticipatory terms. It ensures minimal        tilting by controlling the actuator by anticipation, and        depending on parameterization, also makes it possible to use        minimal states typed as oversteer or understeer in order to play        on the vehicle responsiveness when cornering.

These minimum states can be calculated separately for each wheel, forexample.

The first minimum state ER_(M1) is obtained by using the prerecordedtable or curve that gives the second minimum state as a function of thevehicle speed to retrieve the value of the first minimum state ER_(M1)that corresponds to the measured vehicle speed VVH, e.g., by linearinterpolation. The first minimum state can be calculated separately forthe front and rear wheels.

The second minimum state ER_(M2) is obtained by using the prerecordedtable or curve that gives the second minimum state as a function of thevehicle speed and the corrected longitudinal acceleration to retrievethe value of the second minimum state ER_(M2) that corresponds to themeasured vehicle speed VVH and the corrected longitudinal acceleration{umlaut over (X)}_(COR), e.g., by linear interpolation.

The third minimum state ER_(M3) is obtained by using the prerecordedtable or curve that gives the third minimum state as a function of thevehicle speed and the corrected transverse acceleration to retrieve thevalue of the third minimum state ER_(M3) that corresponds to themeasured vehicle speed VVH and the corrected transverse accelerationŸ_(COR), e.g., by linear interpolation.

The fourth minimum state ER_(M4) is obtained by using the prerecordedtable or curve that gives the fourth minimum state as a function of theanticipated transverse jerk to retrieve the value of the fourth minimumstate ER_(M4) that corresponds to the anticipated transverse jerk

, e.g., by linear interpolation.

For each wheel, the overall minimum damping state ER_(M) provided by theestimator 27 is then equal to the maximum of the minimum states ER_(M1),ER_(M2), ER_(M3), ER_(M4). In this way an overall minimum damping stateER_(MA), ER_(MB), ER_(MC), ER_(MD) is obtained for the wheels A, B, C,D, respectively.

Each of the two functions, Roadhook and Skyhook, has the informationfrom the four displacement sensors as the main input stream.

For example, for a vehicle traveling at less than 20 km/h without driverdemand, the Skyhook function will order the softest damping possible, asthe absolute modal velocities will be very low. However, in thisscenario, the vehicle is likely to go up and down sidewalks, which arehigh-stress demands for which the vehicle would preferably be in alittle bit stiffer damping state.

Likewise, for a very high vehicle speed (e.g., on the highway), with nodriver demands and on a good road, Skyhook will order soft damping. Thiscan pose a problem for high speeds, because damping may have to becomevery stiff very suddenly, which is not possible with the actuators beingused.

Moreover, Roadhook logic can lag slightly behind driver demands: theanticipatory forces estimated by Roadhook logic are not late, but inorder to change over to a stiff law, the wheel must already haveincreased its displacement speed. But when the wheel is increasing itsdisplacement speed, it is already too late. Therefore, an adequatelystiff damping level must be ensured independently of the wheeldisplacement speed, by incorporating minimum damping states duringlongitudinal and lateral accelerations, as well as during lateral jerk(ahead of accelerations).

In order to improve vehicle comfort, it is preferable to change back toSkyhook logic in stabilized cornering or stabilized longitudinalacceleration scenarios. This makes it possible to temper absolute bodyvelocities. However, one must take care in these scenarios not tounder-damp the vehicle too much, because these situations arepotentially dangerous (a curve that gets tighter, a road surface thatdeteriorates on a curve, etc.). Minimum states will therefore be appliedduring stabilized accelerations so that the Skyhook function can be usedsafely.

Lastly, minimum states during jerk make it possible to incorporateflexibility in responsiveness and driving pleasure when cornering.

Damping Law Control

A control module 28 receives as input the damping setpoint law ER_(CA),ER_(CB), ER_(CC), ER_(CD), provided by the estimator 22 and the overallminimum damping state ER_(MA), ER_(MB), ER_(MC), ER_(MD), provided bythe estimator 27, for the wheels A, B, C, D, respectively, and fromthese states it calculates the damping control states ER_(A), ER_(B),ER_(C), ER_(D) for the wheels A, B, C, D by taking the maximum of thedamping setpoint law and the overall minimum damping state for eachwheel:ER _(A)=max(ER _(CA) ,ER _(MA))ER _(B)=max(ER _(CB) ,ER _(MB))ER _(C)=max(ER _(CC) ,ER _(MC))ER _(D)=max(ER _(CD) ,ER _(MD))

These control states ER_(A), ER_(B), ER_(C), ER_(D) determine thedamping law applied by each damper AM and are the control magnitudes ERsent on the control input COM to the actuator for each damper AM foreach wheel A, B, C, D.

The control states ER_(A), ER_(B), ER_(C), ER_(D) are additionally sentto the estimator 12 input for the actual state ER of the actuator.

Additional functions are described below, which can be provided in thedevice for calculating the damper control states ER_(A), ER_(B), ER_(C),ER_(D) of the dampers for the wheels A, B, C, D.

Addressing Impacts

Impacts are detected on the front wheels. It is not possible toanticipate the obstacle. Thus, an obstacle will be detected when thefront wheels encounter it. An impact is detected by monitoring thedisplacement speed of the front wheels of the vehicle.

The distinguishing feature of an impact is the major displacement speedit generates at the wheels. The obstacle may be low in amplitude (e.g.,a shallow pothole), but it generates an impact because the wheels aredisplaced very quickly.

In FIG. 16, an estimator 50 is provided to calculate a setpoint state ordamping setpoint law ERP in case an impact is detected. This estimator50 receives as input:

-   -   the front wheel A, B displacements DEB(A), DEB(B), provided by        the displacement sensors CAP-DEB,    -   the front wheel A, B displacement speed VDEB(A), VDEB(B),    -   the measured vehicle speed VVH,    -   the corrected transverse acceleration Ÿ_(COR),    -   the weighting coefficient α for the first comfort forces F_(z1),        F_(θ1) and F_(φ1) and the second handling forces F_(z2), c_(θ2)        and c_(φ2).

Impact detection and processing is done independently on the left andright wheels of the vehicle. If an impact is detected only on the rightfront wheel, then impact processing will be activated only on theright-side wheels. If an impact is detected only on the front leftwheel, then impact processing will be activated only on the left-sidewheels.

The estimator 50 comprises:

-   -   a module 51 to detect impacts based on displacements DEB and        displacement speeds VDEB,    -   a module 52 for calculating an activation lag time and a signal        to disable processing as a function of the vehicle speed VVH,        the corrected transverse acceleration Ÿ_(COR) and the weighting        coefficient α.    -   a module 53 for processing impacts on the left side,    -   a module 54 for processing impacts on the right side.

Impact Detection

An impact detection threshold SDP is predefined in module 51. When thefront wheel displacement speed VDEB(A) on one side of the vehicle, e.g.,the left side in what follows, is greater in absolute value than theimpact detection threshold SDP, a Boolean logic signal P for probableimpact detection is set at 1, whereas if the front wheel displacementspeed VDEB(A) is less than or equal in absolute value to the impactdetection threshold SDP, the probable impact detection signal P is at 0.

In order to optimize the adjustment, this impact detection threshold SDPis parameterized according to the vehicle speed VVH. A prerecordedtable, curve or map that gives the impact detection threshold as afunction of the vehicle speed is used to retrieve the value of theimpact detection threshold SDP that corresponds to the vehicle speedVVH, e.g., by linear interpolation. For example, at very high speedsVVH, almost any obstacle may generate a high displacement speed. At highvehicle speeds, the impact detection threshold SDP must therefore beincreased so as to not implement ill-timed control processing of roadstresses that do not correspond to actual impacts.

After an impact, displacement speeds can oscillate for a few moments,and may go over the threshold SDP multiple times due to a single initialimpact. A dwell time TEMP that is activated the first time the thresholdSDP is exceeded then makes it possible to avoid detecting multipleimpacts for a single encounter with an obstacle.

For example, when an impact is detected, it is only validated if it isdetected for longer than a prescribed impact detection time DDP, e.g.,15 milliseconds.

Disabling Impact Detection

An impact detection disabling signal S=SIDP is generated as being equalto 1 in order to disable impact detection when at least one of the frontdisplacements DEB(A), DEB(B) becomes less than a first stop thresholdSDEB1 or greater than a second stop threshold SDEB2, and is otherwiseequal to 0.

Actually, during forceful body movements, displacement can be such thatthe train will abut its stops. Slamming into the stops generates a highdisplacement speed that is capable of activating the impact processingfunction. If this function is activated in this scenario, it willprescribe soft damping states at the rear for a certain time. Theproblem is that if the damping state changes to soft while the train isabutting its stops, then the body movements will not be curbed at all,and excessive heaving of the rear axle will occur. Therefore, impactdetection will be disabled in this scenario. To do this, the wheeldisplacement values are monitored. When these displacements exceed theparameter-adaptive threshold SDEB1 or SDEB2 (which corresponds to thepossible displacement path of the wheel prior to contact with thecompression or extension stops), impact detection is disabled.

The module 51 generates an impact validation signal W from the probableimpact detection signal P as follows.

A validatable impact signal Q and the impact validation signal W aregenerated during the calculation cycle n as a function of their valuesduring the preceding cycle n−1 and an elapsed dwell-time TEMP signal T,calculated from the probable impact detection signal P.

The validatable impact signal Q is initialized at 1.

An elapsed dwell time TEMP signal T is set at 1 if the probable impactdetection signal P remained at 0 since its last falling edge for a timegreater than the dwell time TEMP. Otherwise the elapsed dwell time TEMPsignal T is 0.

The validatable impact signal Q is equal to:Q′= Q· W·T+Q· W· T+Q· W· T+Q· W·Twhere Q′ designates the state in the following cycle, and indicates thecomplement.

The impact validation signal W is then set at 1, meaning that an impacthas indeed been detected, when simultaneously

-   -   the probable impact detection signal P is at 1 for a prescribed        number of consecutive cycles, e.g. 3 cycles making up the time        period DDP, the validatable impact signal Q is 1,    -   the impact detection disable signal S=SIDP is 0, indicating no        disabling,    -   the corrected transverse acceleration Ÿ_(COR) is less in        absolute value than a prescribed disable threshold SY for the        corrected transverse acceleration: |Ÿ_(COR)|<SY, thus        W=P·Q· S ·(|Ÿ _(COR) |<SY)

Impact Encounter Time Lag and Disabling for Low Speeds

In order to help the rear wheels take the impact, it is imperative thatthey encounter the obstacle in a soft damping state. To do this, theimpact processing function must calculate the precise instant of theencounter by the rear wheels.

When the impact is detected on the front wheels, i.e., when the impactvalidation signal W is set at 1, the module 52 calculates the time lagDEL for the encounter by the rear wheels with respect to the frontwheels, generally as follows:DEL=(e/VVH)−TRwhere TR is a prescribed reaction time corresponding to the time neededfor the actuators to change to a soft state.

If the vehicle speed VVH is too low (less than or equal to a vehiclespeed threshold SVVH) or if the weighting coefficient α for the firstcomfort forces F_(z1), F_(θ1) and F_(φ1) and the second handling forcesF_(z2), c_(θ2) and c_(φ2) is too large (greater than or equal to aweighting coefficient threshold SCOEFF), a disabling signal SINV for lowspeeds is set at 1, and the rear-wheel time lag DEL is equal to amaximum prescribed value DELMAX.

Control Processes for the Rear Wheels

As soon as the impact is detected on the left front wheel, a dwell timeis activated during the rear-wheel time lag DEL in the processing module53 for the left wheels. At the end of this dwell time, a prescribed softdamping setpoint state ESP is applied to the left rear wheel of thevehicle for a prescribed application time, so that the impact isappropriately damped by the left rear wheel damper. The damping stateselected and the duration of application are parameter-adaptive controldata.

Control Processes for the Front Wheels

As soon as the impact is detected on the left front wheel, controlprocessing for the left front wheel can only be post-processing. Thepurpose of the latter is to reduce shaking in the train and to curbwheel movement and rebound just after the obstacle.

Post-processing for the front wheels consists in applying a prescribedstiff damping setpoint state ERP for a prescribed application time. Thedamping state selected and the duration of application areparameter-adaptive control data.

Post-Processing for the Front and Rear Wheels

At the end of the rear wheel control process, impact post-processing isimplemented on the front wheels and the rear wheels. In order to reducewheel movement due to the obstacle, a prescribed stiff damping setpointstate ERP is applied to the rear wheels for a prescribed post-processingtime. The damping state selected and the duration of the front and rearwheel post-processing are parameter-adaptive control data.

Disabling the Control Process

The impact processing modules 53, 54 produce imposed impact dampingstates ERP that can take precedence over the damping states ER orderedby the Skyhook and Roadhook functions.

In certain scenarios, these imposed impact damping states ERP can eitherdowngrade the comfort of the vehicle or pose a safety hazard. This iswhy impact processing is subject to being disabled, if need be.

When the vehicle is traveling over a very deteriorated road with highfrequency stresses (paved road stresses), wheel displacement speeds willreach high levels that can activate the impact processing function.

If this function is activated, it will apply impact damping setpointstates ERP that will be stiff for a set time on all four wheels. On apaved road, these stiff damping states ERP will cause discomfort duringthe entire post-processing time. The ideal strategy for not generatingbody movement on paved roads is actually to remain in the softestpossible damping law.

Thus, impact processing will be disabled as soon as a set number ofimpacts, e.g., three, are detected in a short, set time period, e.g., upto the impact validation signal W. The resulting disablement will have aparameter-adaptive duration.

Another possible case for disabling the control process is vehiclespeeds VVH that are too low. Moreover, when the AMVAR integration logicis in “handling” mode, i.e., when Roadhook logic is activated and theweighting coefficient α is equal to 1 or close to 1, impact processingis also disabled (see supra SINV).

Another instance of disabling the control process can be provided forthe safety of the vehicle. During high driver demand or when the vehicleis settled into stabilized cornering, applying a soft damping state canbe hazardous for road-holding. In these driving conditions, Roadhooklogic optimizing vehicle handling absolutely must not be deactivated byother functions. This is a matter of individual safety. Thus, thelateral acceleration of the vehicle is monitored, for one: when itcrosses a certain parameter-adaptive threshold, impact processing isdisabled as described above when the corrected transverse accelerationŸ_(COR) has an absolute value greater than or equal to the prescribeddisable threshold SY for corrected transverse acceleration:|Ÿ_(COR)|≧SY.

The module 52 generates an impact processing disable signal INHIB, equalto 1, in order to disable impact processing by the modules 53 and 54when either or both of the following conditions are met:

-   -   a preset number of impacts, represented by rising edges of the        impact validation signal W, is detected in a preset time period;    -   the disable signal SINV for low speeds is set at 1, to indicate        that the vehicle speed VVH is too low or that the weighting        coefficient α for the first comfort forces F_(z1), F_(θ1) and        F_(φ1) and the second handling forces F_(z2), c_(θ2) and c_(φ2)        is too large, indicating that Roadhook logic is operative,        |Ÿ _(COR) |≧SY.

The rear-wheel time lag DEL and the impact processing disable signalINHIB are sent to two inputs for each of the processing modules 53, 54.Each of the modules 53, 54 also has a clock input CLK linked by a logicoperator AND with the impact validation signal W input W(A) for the leftfront wheel A and the impact validation signal W input W(B) for theright front wheel B, respectively, to indicate the calculation frequencyof the modules 53 and 54. A clock input is also provided for each of theblocks, estimators and modules shown in the figures.

Should the estimator 50 be provided, the latter provides setpoint statesERP in the event of impact detection to another input of the controlmodule 28, that is, the setpoint states ERP_(A), ERP_(B), ERP_(C),ERP_(D) for the wheels A, B, C, D.

From these states, the control module 28 calculates the damping controlstates ER_(A), ER_(B), ER_(C), ER_(D) for the wheels A, B, C, D bytaking the maximum of the damping control states ER_(C), ERP and theoverall minimum damping state for each wheel:ER _(A)=max(ER _(CA) ,ER _(PA) ,ER _(MA))ER _(B)=max(ER _(CB) ,ER _(PB) ,ER _(MB))ER _(C)=max(ER _(CC) ,ER _(PC) ,ER _(MC))ER _(D)=max(ER _(CD) ,ER _(PD) ,ER _(MD))

Addressing Large-Amplitude Movements (Logic for Large Displacements)

Detection of large displacements and high displacement speeds isprovided for the front wheels or the rear wheels. The goal is to detectthe obstacles that can generate large amplitudes in body movement asearly as possible in forward and/or reverse drive. Detection is providedfor these scenarios in order to handle obstacles that exert stresssimultaneously on the right and left wheels of the front or rear train.These obstacles can be detected as compression for speed bumps or asextension for catch drains or sizable dips. In forward drive, this kindof obstacle will generate large-amplitude displacements and displacementspeeds on the front wheels.

In FIG. 17, an estimator 60 is provided to calculate a setpoint state ordamping setpoint law ERGD in the event that a large-amplitude wheelmovement is detected. This estimator 60 receives as input:

-   -   the front displacements DEB(A), DEB(B) of the front wheels A, B        and the displacements DEB(C), DEB(D) of the back wheels C, D,        which can be those filtered DEBF(A), DEBF(B), DEBF(C), DEBF(D)        by the filter 13, for example, using the displacements DEB(A),        DEB(B), DEB(C), DEB(D) provided by the displacement sensors        CAP-DEB,    -   the front displacement speeds VDEB(A), VDEB(B) of the front        wheels A, B and the displacement speeds DEB(C), DEB(D) of the        rear wheels C, D, provided by the derivation module DER,    -   the measured vehicle speed VVH,    -   the body bounce level NTC provided by the estimator 24.

The estimator 60 implements a logic for detecting and processinglarge-amplitude movements, and includes:

-   -   a detection module 61 for large-amplitude wheel movements,    -   a module 62 for enabling and disabling the detection of        large-amplitude wheel movements,    -   a module 63 for calculating a processing coefficient χ for        large-amplitude wheel movements,    -   a module 64 for calculating the setpoint state or damping        setpoint law ERGD for large-amplitude wheel movements.

Detecting Large-Amplitude Wheel Movements

A first detection threshold SDGD for large displacements and a seconddetection threshold SVGD for high displacement speeds are predefined inthe module 61.

When the left front wheel displacement DEBF(A) crosses the firstdetection threshold SDGD for large displacements, the right front wheeldisplacement DEBF(B) crosses the first detection threshold SDGD forlarge displacements, the left front wheel displacement speed VDEB(A)crosses the second detection threshold SVGD for high displacementspeeds, and the right front wheel displacement speed VDEB(B) crosses thesecond detection threshold SVGD for high displacement speeds alltogether, then a first detection signal SDGAV for large front movementsis set at 1 to indicate that a large-amplitude movement has beendetected on the front wheels.

The same applies for a second detection signal SDGAR for large rearmovements, which is set at 1 to indicate that a large-amplitude wheelmovement has been detected on the rear wheels, when the fourthreshold-crossing conditions are fulfilled by the displacements DEBF(D)and DEBF(C) and the displacement speeds VDEB(D) and VDEB(C) for the rearwheels.

The first and second thresholds SDGD and SVGD can be different for thefront and the rear. The first and/or second threshold crossings SDGD,SVGD can be the displacement and/or the displacement speed crossingbelow the lower threshold SDGD, SVGD, e.g., on the damper extensionstroke, and/or the displacement and/or the displacement speed crossingabove another threshold SDGD greater than the lower threshold SDGD,SVGD, e.g., on the damper compression stroke.

A detection signal SGD for large movements is set at 1 to indicate thata large-amplitude wheel movement has been detected on the wheels whenthe first detection signal SDGDAV for large movements in front and/orthe second detection signal SDGDAR for large movements at the rearregisters 1. The large-movement detection signal SDG is sent by thedetection module 61 to the enable and disable module 62.

For greater precision and to avoid ill-timed control processing, thefirst large-displacement detection threshold SDGD and the second largedisplacement speed detection threshold SVGD are parameterized accordingto the vehicle speed VVH. For example, for each of these thresholdsSDGD, SVGD, the prerecorded table, curve or map that gives the detectionthreshold as a function of the vehicle speed is used to retrieve thevalue of the detection threshold SDGD, SVGD that corresponds to thevehicle speed VVH, e.g., by linear interpolation.

Disabling the Detection of Large Wheel Movements

An enable or disable signal INSGD for detecting large-amplitude wheelmovements is generated by the module 62 as being equal to 0 in order todisable detection when one or more of the following conditions is met:

-   -   the weighting coefficient α for the first comfort forces F_(z1),        F_(θ1) and F_(φ1) and the second handling forces F_(z2), c_(θ2)        and c_(φ2) is too large (greater than a weighting coefficient        threshold SCOEFF2, e.g., zero), indicating that Roadhook logic        is at least partially operative,    -   the bounce level NTC is greater than a prescribed bounce level        threshold SNTC.

If none of the disablement conditions is met and if the large-movementdetection signal SGD is 1 to indicate that a large-amplitude wheelmovement has been detected, then the signal INSGD adopts the value 1,enabling the detection of large-amplitude wheel movements.

In the first case of disablement (weighting coefficient α), at thedriver's demand, it is safer to let Roadhook logic act and react inresponse to road stresses in order to improve body attitude andparticularly in order to maximize wheel contact with the road. IfRoadhook logic wants to transmit an instruction to change to softdamping states, it must not be kept from doing so. This is why thedetection and processing of large-amplitude movements is disabled whenRoadhook logic is active.

In the second case of disablement (bounce level NTC), processinglarge-amplitude movements can be detrimental to vibrational comfort,because a damping state that is too firm will transfer roadirregularities to the body, and thus will not filter bounces and joltsgenerated by this road. This is why it is preferable to disable theprocessing logic for large-amplitude movements when the road isdeteriorated. A state-of-the-road recognition logic is used, based onbandpass filtering of displacements DEB. As indicated above forcalculating the level NMC of low frequencies and the level NTC ofbouncing, filtering around the body mode (around 1 Hz) and in the bounceband (between 3 and 8 Hz) is used to characterize the state of the road(good road, road with a good surface that generates body movements, roadwith a deteriorated but flat surface, road with a deteriorated surfacethat generates body movements). For disablement, the bounce levelcalculated from filtering between 3 and 8 Hz is used. The prescribedthreshold SNTC for the bounce level is parameter-adaptive. In this way,the trade-off between body attitude and vibrational comfort isoptimized.

Control Processing for Large Wheel Movements

From the enable or disable signal INSGD for large-amplitude wheelmovement detection, the estimator 63 calculates the processingcoefficient χ for large-amplitude wheel movement.

The processing coefficient χ is a variable greater than or equal to 0and less than or equal to 1. The processing coefficient χ is 0 bydefault. When the signal INSGD changes from the state 0 in whichlarge-amplitude wheel movement detection is disabled to the state 1 inwhich large-amplitude wheel movement detection is enabled, theprocessing coefficient χ increases from 0 to 1 with a prescribed upwardslope, e.g., that can be parameterized by a first dwell time TEMP1 atthe input of module 63. The processing coefficient χ is then kept at itsmaximum value 1 for a prescribed time, e.g., that can be parameterizedby a second dwell time TEMP2 at the input of module 63, and goes backdown to 0 with a prescribed downslope, e.g., that can be parameterizedby a third dwell time TEMP at the input of module 63.

Minimum States in Cases where Large Wheel Movements are Detected

The module 64 receives the processing coefficient χ for large-amplitudewheel movement and the vehicle speed VVH, and from them it calculatesthe damping setpoint law ERGD in the event that a large amplitude wheelmovement is detected.

Large-amplitude wheel movement situations are processed by using minimumdamping setpoint states ERGD.

The various parameters involved in calculating the processingcoefficient χ make it possible to control the exact instant and theexact length of time during which the minimum damping states ERGD willbe applied by the module 64.

These minimum states ERGD can be parameterized according to the vehiclespeed VVH in order to optimize the trade-off between body attitude andvibrational comfort, regardless of the vehicle speed: the minimum statesto be used are less at 30 km/h for going over speed bumps than at ahigher speed where a stress from the road that creates a largedisplacement will require high minimum states. The minimum states ERGDcan also be calculated separately for the front wheels and the rearwheels.

The damping control states ERGD are calculated, for example, as follows:

-   -   an intermediate state ERGD-INTER of large-amplitude wheel        movement (with an intermediate damping law number) is retrieved        from a prerecorded table or curve that gives this intermediate        state as a function of the vehicle speed, with the value        ERGD-INTER of the intermediate state of large-amplitude wheel        movement corresponding to the vehicle speed, e.g., by linear        interpolation.    -   the large-amplitude wheel movement damping control state ERGD is        then equal to the intermediate damping state ERGD-INTER        multiplied by the large-amplitude wheel movement processing        coefficient χ, rounded to the nearest damping law number, for        example.

Should the estimator 60 be provided, the latter supplies the dampingcontrol states ERGD in the event that a large-amplitude wheel movementis detected, i.e., for the wheels A, B, C, D, the control statesERP_(A), ERP_(B), ERP_(C), ERP_(D), to another input of the controlmodule 28.

From these states, the control module 28 calculates the damper controlstates ERGD_(A), ERGD_(B), ERGD_(C), ERGD_(D) for the wheels A, B, C, Dby taking the maximum of the damping control states ER_(C), ERGD (andERP, if need be, to take impacts into account) and the minimum overalldamping state ERM:ER _(A)=max(ER _(CA) ,ERGD _(A) ,ER _(MA))ER _(B)=max(ER _(CB) ,ERGD _(B) ,ER _(MB))ER _(C)=max(ER _(CC) ,ERGD _(C) ,ER _(MC))ER _(D)=max(ER _(CD) ,ERGD _(D) ,ER _(MD))

1. Suspension control device with variable damping for a motor vehiclebody on its wheels, said device comprising: a computer adapted tocalculate a control magnitude of an actuator of at least one damper withvariable damping of a suspension of the vehicle as a function of atleast one body modal speed, calculated from at least one body modalacceleration determined on the vehicle, at least one displacement sensorproviding a displacement measurement which is a measurement of adisplacement of a wheel of the vehicle with respect to the vehicle body,a first calculation means for calculating the body modal accelerationfrom the displacement measurement provided by the displacement sensor,wherein the first calculation means for calculating the body modalacceleration comprises: a suspension force estimator providing anestimation of at least one force exerted by a suspension of said wheelon the body as a function of at least the displacement measurementprovided by the displacement sensor, and a second calculation means forcalculating the body modal acceleration as a function of at least thesuspension force provided by said suspension force estimator.
 2. Controldevice according to claim 1, wherein the suspension force estimatorcomprises: a derivator module calculating a displacement speed from thedisplacement measurement provided by the displacement sensor, a dampingforce estimator providing an estimation of a damping force of the damperas a function of the displacement speed provided by the derivator moduleand a memorized current damping law of the damper, a dry friction forceestimator providing an estimation of a dry friction force as a functionof the displacement speed, a flexion force estimator providing anestimation of a flexion force of suspension springs and stops of thedamper as a function of the displacement value and a determined staticattitude of the body.
 3. Control device according to claim 2, whereinthe dry friction force estimator provides the estimation of the dryfriction force as a hyperbolic tangential or circular tangent functionof the displacement speed divided by a fixed value, this function beingmultiplied by a prescribed multiplying factor.
 4. Control deviceaccording to claim 2, wherein the flexion force estimator comprises: astatic attitude calculation module for calculating the static attitudeof the vehicle as a function of the displacement value, an adder forcalculating a summed value of the displacement value and the staticattitude, an absolute flexion force calculation module for calculatingan absolute flexion force of suspension springs and stops of the damperas a function of said summed value, a static flexion force calculationmodule for calculating a static flexion force on said wheel as afunction of the static attitude, a subtractor providing said flexionforce of suspension springs and stops by subtracting the static flexionforce from the absolute flexion force of suspension springs and stops.5. Suspension control device according to claim 4, wherein adisplacement sensor is provided for each of the two front wheels and thetwo rear wheels, and the static attitude calculation module has a meansfor calculating the front static attitude and the rear static attitudeof the vehicle, as being the mean displacement of the front wheeldisplacements and the rear wheel displacements, respectively, filtratedby a low-pass filter, a front attitude offset constant and a rearattitude offset constant, respectively, being added to this filteredmean displacement.
 6. Control device according to claim 1, wherein thefirst calculation means further comprises a roll torque estimatorproviding an estimation of a roll torque and/or an estimator of a pitchtorque.
 7. Control device according to claim 6, wherein the firstcalculation means has: a means for calculating a transverse accelerationreset value RECT, a sensor of the vehicle body transverse accelerationACCT; the roll torque estimator calculating said roll torque c_(θ) usingthe formula:c _(θ)=(ACCT−RECT)·(MTOT)·d(G,CR) where MTOT is the vehicle mass, andd(G, CR) is the predetermined distance between the center of gravity (G)of the body and its roll center (CR).
 8. Control device according toclaim 6, wherein the first calculation means has: a means forcalculating a longitudinal acceleration reset value RECL, a sensor ofthe longitudinal acceleration ACCL of the vehicle body, the estimator ofthe pitch torque calculating said pitch torque c_(φ) using the formula:c _(φ)=(ACCL−RECL)·(MTOT)·hG+c _(φB), where MTOT is the vehicle mass, hGis the predetermined height between the center of gravity (G) of thebody and its pitch center (CT), and c_(φB) is the component of the pitchtorque attributable to the Brouilhet effect.
 9. Control device accordingto claim 8, wherein the component c_(φB) of the pitch torqueattributable to the Brouilhet effect is calculated as a function of abraking information unit provided by a determination module as afunction of a master cylinder pressure value provided by a mastercylinder pressure sensor.
 10. Control device according to claim 1, whichcomprises a body modal acceleration filter that eliminates at least thelow frequencies of the body modal acceleration provided by the firstcalculation means and a third means for calculating the body modalvelocity from the filtered body modal acceleration provided by the firstfilter.
 11. Control device according to claim 10, wherein the low cutofffrequency of the body modal acceleration filter is greater than or equalto 0.1 Hz.
 12. Control device according to claim 1, wherein the firstmeans for calculating the body modal acceleration comprises adisplacement measurement filter that eliminates at least the lowfrequencies from the displacement measurement provided by thedisplacement sensor.
 13. Control device according to claim 12, whereinthe low cutoff frequency of the displacement measurement filter isgreater than or equal to 0.2 Hz.
 14. Control device according to claim1, wherein the control magnitude is a damping law determined from aplurality of different damping laws that impose the damper force as afunction of its displacement speed.
 15. Motor vehicle having a body,wheels, a suspension of the body on the wheels, and a suspension controldevice according to claim
 1. 16. Production method for equipping a motorvehicle, the motor vehicle being equipped with wheels, a body, asuspension having at least one damper with variable damping of the bodyon the wheels, said method comprising: providing the suspension controldevice according to claim 1, mounting the computer on the vehicle, andprogramming the computer using at least one program having programinstructions that employ the calculating means of the suspension controldevice according to claim
 1. 17. Computer-readable medium carrying acomputer program for controlling a computer, having program instructionsfor calculating a body modal acceleration from a displacementmeasurement provided by a wheel displacement sensor of a wheel of avehicle body, for calculating a body modal velocity as a function of atleast this body modal acceleration, and for calculating a controlmagnitude of an actuator of a damper of a suspension of the wheel as afunction of this body modal speed, when it is employed in a suspensioncontrol device according to claim 1, wherein the computer programcomprises: a suspension force estimator providing an estimation of atleast one force exerted by a suspension of the wheel as a function of atleast the displacement measurement provided by the displacement sensor,and a calculation means for calculating the body modal acceleration as afunction of at least a suspension force provided by the suspension forceestimator.
 18. Computer-readable medium according to claim 17, whereinthe suspension force estimator comprises: a derivator module calculatinga displacement speed from the displacement measurement provided by thedisplacement sensor, a damping force estimator providing an estimationof a damping force of the damper as a function of the displacement speedprovided by the derivator module and a memorized current damping law ofthe damper, a dry friction force estimator providing an estimation of adry friction force as a function of the displacement speed, a flexionforce estimator providing an estimation of a flexion force of suspensionsprings and stops of the damper as a function of the displacement valueand a determined static attitude of the body.